We are hiring for an AI Developer / DevOps Engineer – Azure, AWS & CI/CD. This role focuses on cloud infrastructure, DevOps automation, and AI-driven solutions across Azure and AWS environments.

The ideal candidate has 10+ years of DevOps experience with strong expertise in cloud architecture, CI/CD, Infrastructure as Code, and Python-based automation.

## What you bring

- 10+ years of DevOps experience with Azure and AWS
- Strong hands-on experience with Jenkins, Git, Ansible, and CI/CD pipeline automation
- Expertise in Infrastructure as Code using Terraform, ARM templates, Bicep, and CloudFormation
- Strong knowledge of Azure architecture, networking, VMs, storage, and disaster recovery
- Experience with Kubernetes, OpenShift, and Docker
- Scripting skills in Python, Ruby, or Perl
- Knowledge of GitHub, GitLab, and code management practices
- Strong understanding of cloud security, IAM, RBAC, and compliance
- Experience with Azure DevOps, GitHub Actions, and cloud monitoring tools
- Knowledge of Azure SQL, Cosmos DB, Azure Monitor, and Log Analytics

## What you'll do

- Design, implement, and support cloud infrastructure and DevOps tools
- Build and maintain CI/CD build and release pipelines
- Automate infrastructure provisioning across Azure and AWS
- Establish deployment standards and DevOps best practices
- Onboard applications onto automated CI/CD pipelines
- Define and improve development, testing, release, and support processes
- Troubleshoot infrastructure and application issues
- Monitor DevOps processes and ensure security, reliability, and performance
- Support AI/ML automation and cloud-based AI solutions where required

## Nice to have

- Experience building and deploying GenAI/LLM-based applications
- Knowledge of FastAPI, PyTorch, Hugging Face, LangChain, Spark, and Kafka
- Experience with GPU workloads, Azure ML, AWS SageMaker, or Bedrock
- Exposure to Maven, Gradle, JFrog Artifactory, and Cucumber
- Multi-cloud experience
- Azure or AWS DevOps and Solutions Architect certifications

We're looking for a Senior AI Agent Developer to lead the design, build, and support of enterprise conversational AI agents and the web experiences around them. You'll own key parts of the architecture on Google Cloud Platform (GECX / Dialogflow CX), connect agents to Azure, Google Cloud and ServiceNow, and set the standards for how agents, fulfillment services, and front-end interfaces are built, tested, and released. You'll also mentor engineers and work closely with product, platform, and operations teams.

## Agent Architecture and Development

- Lead the design of conversational flows, route groups, intents, and LLM-powered tools in GECX / Dialogflow CX, and set patterns for agents built with Google's Agent Development Kit (ADK).
- Make architecture decisions for agent orchestration, tool design, and handoffs between agents, fulfillment services, and human agents.
- Lead the design of Contact Center AI (CCAI) solutions, including integration with IVR platforms such as Genesys and Amazon Connect.
- Define prompt engineering and intent classification standards and evaluate changes against measurable quality criteria.

## Backend and Integration

- Design and build REST APIs, webhooks, and services in Python (primary) with .NET or Node.js that connect agents to ServiceNow, Azure systems, and IVR platforms.
- Establish API contracts, versioning, and error-handling standards, including MCP integration patterns.
- Write and optimize SQL for agent lookups, reporting, and conversational analytics.

## Front End

- Lead the development of responsive, accessible interfaces using HTML, CSS, and TypeScript with React or Angular.
- Set front-end patterns for API connection, loading states, error handling, and session management in the browser.
- Own security practices for browser-facing code, including CORS, XSS prevention, and secure handling of tokens and secrets.
- Build internal dashboards for agent analytics, test results, and admin tasks.

## Delivery, Quality, and Operations

- Own and improve Azure DevOps pipelines that validate and deploy agent configurations, fulfillment services, and front-end builds. Review and approve changes to YAML pipelines.
- Define infrastructure as code standards with Terraform for the agent platform, fulfillment services, and supporting cloud resources, and review changes to Terraform modules.
- Define the testing strategy across unit tests, webhook API tests, dialog flow regression tests, and front-end component tests. Drive coverage targets and quality gates.
- Lead incident investigation and root-cause analysis for production issues and failed test runs. Document findings and drive follow-through.
- Monitor agent performance and reliability and contribute to observability and AIOps practices.

## Leadership and Collaboration

- Mentor junior and mid-level developers through code reviews, pairing, and technical guidance.
- Participate in and help lead sprint planning, backlog refinement, and Program Increment (PI) planning within a SAFe environment.
- Partner with product owners and stakeholders to translate business requirements into technical designs and realistic delivery plans.
- Keep architecture diagrams, flow designs, API documentation, and runbooks current, and set documentation standards for the team.

## Required Qualifications

- Bachelor's degree in computer science, IT, or a related field, or equivalent practical experience
- 8+ years of software engineering experience, including at least 1 year building production conversational AI or LLM-based applications
- Advanced proficiency in Python, with working proficiency in .NET and JavaScript or TypeScript
- Strong experience with REST APIs, JSON, webhooks, MCP, and calling APIs from browser applications
- Hands-on experience with Dialogflow CX or GECX, or comparable conversational AI platforms
- Hands-on experience with Contact Center AI (CCAI) solutions or experience with IVR platforms such as Genesys or Amazon Connect
- Strong SQL skills.
- Experience designing and maintaining automated test suites using frameworks such as PyTest, Jest, or xUnit
- Experience with Git, CI/CD pipelines, and code review practices
- Experience with containers and infrastructure as code (Docker, Kubernetes, or Terraform)
- Excellent written and verbal communication, including the ability to explain technical trade-offs to non-technical stakeholders.

## Preferred Qualifications

- Experience building agents with Google's Agent Development Kit (ADK) or similar agent frameworks
- Experience designing prompt strategies, evaluation methods, or intent classification for LLM-based systems
- Experience leading front-end testing with Playwright, Cypress, or Selenium
- Experience with Azure DevOps pipelines or another enterprise CI/CD tool
- Experience with ServiceNow (REST APIs, Flow Designer) or .NET (C#)
- Working knowledge of OAuth2, API keys, secrets management, and browser security
- Experience with SAFe or other scaled Agile frameworks
- Experience with containers (Docker, Kubernetes)
- Experience with serverless platforms (Cloud Run, Azure Functions)
- Interest in or experience with SRE, observability, and AIOps

## Tooling and Environment

- Conversational AI and Cloud: Google Cloud Platform (GECX / Dialogflow CX), Microsoft Azure
- Contact Center: Contact Center AI (CCAI), Genesys, Amazon Connect
- Infrastructure as Code: Terraform
- Back end: Python 3.x (primary), .NET (C#), Node.js, SQL
- Front end: HTML, CSS, TypeScript / JavaScript, React or Angular
- DevOps and Testing: Azure DevOps (Pipelines, Repos), Git, API, unit, and UI testing frameworks
- Enterprise Platforms: ServiceNow (REST APIs, Flow Designer)
- Agile: SAFe, Jira / Azure Boards
- IDEs: Visual Studio Code, Antigravity

location: New York, New York
job type: Contract
salary: $65 - 75 per hour
work hours: 9am to 6pm
education: Bachelors

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.

Join a growing executive leadership community supporting C-suite executives, business leaders, technology executives, data and analytics leaders, and AI decision-makers focused on AI, Generative AI, Agentic AI, data science, analytics, and data-driven business transformation.

Work Model: Hybrid (mandatory in-office attendance). We are seeking local candidates currently residing in the San Francisco Bay/Santa Clara Area. Relocation is not available for this position.

## Key Responsibilities

- Build and grow a community of senior executives, business leaders, and technology leaders focused on AI, data, and analytics.
- Manage executive engagement, including outreach, invitations, onboarding, communications, and relationship management.
- Coordinate executive roundtables, leadership forums, webinars, and community events, ensuring a high-quality attendee experience.
- Partner with external agencies, vendors, and internal stakeholders to deliver successful executive programs and events.
- Develop executive-facing communications, including invitations, newsletters, community updates, LinkedIn content, and thought leadership materials.
- Manage content calendars and coordinate production of articles, presentations, videos, and executive insights related to AI, data science, and analytics.
- Support the ongoing management of the community portal, digital content libraries, and engagement platforms.
- Analyze community, event, and engagement metrics to provide insights and recommendations that drive program growth and effectiveness.
- Manage program plans, schedules, budgets, trackers, risks, dependencies, and vendor relationships across multiple workstreams.
- Collaborate with senior executives, subject matter experts, consulting leaders, and cross-functional teams to deliver an exceptional executive community experience.

## Requirements

- 3-5 years of experience in Program Management, Project Management, Events, Communications, Account Management, Community Management, Marketing, or Executive Engagement.
- Experience leading cross-functional programs supporting Data & Analytics, Data Science, Artificial Intelligence (AI), Machine Learning (ML), Business Intelligence, or Digital Transformation organizations.
- Experience managing programs, executive initiatives, or client engagements for data analytics, data science, AI, or consulting practices, with the ability to partner effectively with technical teams, business stakeholders, and senior executives.
- Knowledge of data analytics, business intelligence, and core data science technologies, including data visualization, reporting, dashboards, predictive analytics, machine learning, and AI concepts.
- Familiarity with technologies such as Power BI, Tableau, SQL, Python, Microsoft Fabric, Databricks, Snowflake, Azure Data Services, or similar analytics and data platforms is a plus.
- Strong executive communication, stakeholder management, and presentation skills.
- Experience managing multiple projects, executive stakeholders, vendors, and workstreams simultaneously.
- Experience with LinkedIn, content marketing, community platforms, CRM tools, Notion, or similar collaboration tools is an asset.

## Compensation and Benefits

The base compensation range for this role in the posted location is $89,400 to $125,571.

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

## Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

## Job Summary

TDIndustries is an employee-owned company in the mechanical construction, operations, and maintenance industry headquartered in Dallas, Texas. With approximately 3,100 employee-partners across six business units, TDIndustries delivers mechanical construction, building services, facilities management, and manufacturing solutions. The Technology Services team drives innovation through enterprise platforms, digital products, and emerging technologies including artificial intelligence.

The AI Solutions Engineer / Sr. Software Developer will design, develop, and implement AI-powered solutions and software applications that leverage machine learning, large language models, and intelligent automation to solve business challenges across TDIndustries' construction, facilities, and building services operations. This role partners with business stakeholders to identify AI opportunities, builds proof-of-concept solutions, and delivers production-ready applications that integrate with enterprise platforms. The position serves as a technical resource on AI/ML best practices, responsible AI governance, and emerging technologies.

## AI Development

- Design and develop AI-powered applications using large language models (LLMs), including integration with Azure OpenAI, Anthropic Claude, and other foundation model providers
- Build AI agents and agentic AI solutions that autonomously execute multi-step workflows, make decisions, and integrate with enterprise systems
- Leverage Azure AI Foundry and Microsoft Copilot Studio to develop, deploy, and manage AI solutions and custom copilots across the organization
- Implement retrieval-augmented generation (RAG) solutions, vector databases, and semantic search capabilities to enable intelligent document processing and knowledge retrieval
- Develop and optimize prompts, prompt chains, and agentic workflows for production AI applications
- Build machine learning pipelines for predictive analytics, anomaly detection, and classification use cases relevant to construction and facilities operations

## Software Engineering

- Develop full-stack applications using modern frameworks including Python, TypeScript/JavaScript, React, Node.js, etc
- Design and implement RESTful APIs and microservices architectures for AI model serving and application integration
- Embed AI-driven CI/CD and Agile approaches in end-to-end development, leveraging intelligent automation for code review, testing, deployment, and sprint planning
- Integrate AI capabilities with enterprise platforms, including Microsoft Dynamics 365, Power Platform, and Azure cloud services
- Implement CI/CD pipelines, automated testing, and MLOps practices for reliable deployment of AI solutions

## Innovation & Collaboration

- Partner with business stakeholders to identify AI opportunities, translate requirements into technical solutions, and deliver proof-of-concept demonstrations
- Evaluate emerging AI technologies, tools, and frameworks; provide recommendations for adoption
- Support AI governance initiatives including responsible AI policies, data ethics guidelines, and model evaluation frameworks
- Mentor colleagues on AI/ML concepts, tools, and development practices; create documentation and training materials
- Participate in code reviews, architecture discussions, and agile development ceremonies

## Minimum Requirements

- 5-7 years of software development experience, with a current focus on AI/ML development or integration
- Proficiency in AI development, including AI driven CI/CD and Agile frameworks
- Experience with LLM APIs (OpenAI, Azure OpenAI, Anthropic, or similar) and prompt engineering techniques
- Strong full-stack development skills in numerous languages, and modern web frameworks
- Experience with cloud platforms (Azure & GCP preferred) including compute, storage, and AI services
- Proficiency with databases and experience with modern data warehousing solutions

Python and LLM Integration

## Role overview

We are looking for a Junior AI Platform Engineer to help build and maintain AI features in Barq, an enterprise platform for analytics and customer-care applications. You will work with senior engineers on Python services, language-model integration, data preparation, testing, and deployment support.

This role suits an early-career engineer with solid programming fundamentals and evidence of practical learning through projects, internships, or professional work. You will own well-defined tasks with code review and mentoring, while developing experience in model evaluation and reliable AI applications.

## Key responsibilities

- Implement and maintain small Python backend features, API integrations, and utility scripts within established designs.
- Help connect local and cloud language models to application workflows, including structured responses and tool calls, using existing interfaces.
- Prepare and validate training or evaluation datasets, checking formats, missing values, duplicates, and documented data provenance.
- Write and maintain unit and integration tests; reproduce bugs and verify fixes under senior review.
- Run established model evaluations and bounded performance tests, recording inputs, settings, results, failures, and resource measurements.
- Investigate application logs and request traces, document findings, and escalate unclear or cross-component issues with reproducible examples.
- Assist with Docker-based development, CI checks, and deployment verification using approved runbooks and supervision.
- Follow existing authorization, data-handling, and secret-management practices; keep sensitive information out of logs and shared artifacts.
- Update setup guides, test instructions, and change notes, and participate in code reviews and team discussions.

## Scope and support

Senior engineers will guide architecture, security-sensitive changes, production releases, fine-tuning strategy, and GPU resource configuration. You will contribute through scoped implementation, evidence collection, testing, and documented experiments, taking on broader responsibility as your skills develop.

## Required qualifications

- Working knowledge of Python, including functions, classes, exceptions, modules, and common data structures.
- Understanding of HTTP APIs, JSON, and client-server request flows, with experience building or consuming an API in a project.
- Basic SQL skills and familiarity with relational databases and structured data.
- Ability to use Git for branches, commits, and pull requests, and to work from the command line.
- Familiarity with automated testing and a systematic approach to reproducing and debugging problems.
- Basic understanding of LLM prompts, context, structured outputs, and why generated answers and code require validation.
- Ability to explain your own code, respond to review feedback, and communicate progress and blockers clearly.
- Practical evidence of programming ability through personal, academic, open-source, internship, or professional projects. Previous production AI experience is not required.

## Preferred qualifications

- Exposure to FastAPI or another Python web framework, PostgreSQL, and Docker.
- A project involving an LLM API, embeddings, retrieval, or a locally hosted model.
- Familiarity with pytest, GitHub Actions, Linux, or basic asynchronous programming.
- Experience cleaning or transforming data with pandas, SQL, CSV, JSON, or Parquet.
- Exposure to React or TypeScript, Arabic-English AI workflows, or introductory machine-learning coursework.

## Learning opportunities

You will build experience in reliable tool calling, model evaluation, observability, and concurrent application workflows. Depending on project needs, you may assist with supervised fine-tuning experiments, GPU inference, and larger data-processing systems. Prior expertise in these areas is not required.

## Expected outcomes

- Deliver scoped features and bug fixes that pass relevant checks and senior code review.
- Produce reproducible test and evaluation results, with failures and limitations clearly recorded.
- Follow data-access and operational procedures and raise risks or blockers promptly.
- Maintain useful documentation and gradually handle routine debugging and implementation with less supervision.

Company: Crystal Techify
Position: AI & Data Science Engineer
Salary: PKR 200,000+ per month (Negotiable based on experience and skills)
Job Type: Full-Time
Work Mode: Remote
Shift: USA Working Hours (Timing to be discussed)
Experience Required: 3–5+ Years

## Job Overview

Crystal Techify is looking for a highly skilled and experienced AI & Data Science Engineer to join our growing technical team.

The ideal candidate should have strong expertise in Artificial Intelligence (AI), Machine Learning (ML), Data Science, Python, and advanced data analytics.

The selected candidate will work remotely on USA-based projects, develop intelligent AI solutions, build machine learning models, and collaborate with international clients and development teams.

We are seeking a technically strong, analytical, and results-driven professional who can develop scalable, data-driven solutions.

## Artificial Intelligence & Machine Learning

- Design, develop, and deploy AI and machine learning models.
- Build intelligent automation and predictive analytics solutions.
- Develop and optimize machine learning algorithms.
- Work with deep learning and natural language processing (NLP) models.
- Integrate AI solutions into existing applications.

## Data Science & Analytics

- Analyze large datasets to identify patterns and business insights.
- Perform data cleaning, preprocessing, and feature engineering.
- Develop predictive models and statistical analysis solutions.
- Create reports and dashboards for business decision-making.
- Ensure data accuracy, reliability, and quality.

## Generative AI & LLM Development

- Work with Large Language Models (LLMs), including GPT-based applications.
- Develop AI chatbots, virtual assistants, and automation tools.
- Implement Retrieval-Augmented Generation (RAG) solutions.
- Work with AI APIs and model integration.
- Optimize AI model performance and response accuracy.

## Python Development & Data Engineering

- Develop AI and data science applications using Python.
- Work with SQL databases and data pipelines.
- Build scalable data processing workflows.
- Integrate machine learning models with backend systems.
- Maintain and improve existing AI applications.

## Collaboration & Project Delivery

- Collaborate with USA-based clients and technical teams.
- Understand project requirements and provide AI-driven solutions.
- Participate in technical discussions and project meetings.
- Deliver assigned projects within deadlines.
- Maintain proper technical documentation.

## Required Skills & Qualifications

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
- Minimum 3–5 years of professional experience in AI, Machine Learning, or Data Science.
- Strong proficiency in Python, Pandas, NumPy, Scikit-learn, and SQL.
- Hands-on experience with TensorFlow or PyTorch.
- Experience with Generative AI, LLMs, and AI API integrations.
- Understanding of NLP, predictive modeling, and statistical analysis.
- Familiarity with LangChain, vector databases, and RAG architecture.
- Experience with REST APIs and cloud-based environments.
- Strong analytical, problem-solving, and debugging skills.
- Excellent English communication skills.
- Ability to work independently in a remote environment.
- Comfortable collaborating with USA-based teams.

## Preferred Skills

- Experience with AWS, Azure, or Google Cloud.
- Knowledge of MLOps, Docker, and CI/CD pipelines.
- Experience deploying machine learning models into production.
- Familiarity with OpenAI APIs and AI automation frameworks.
- Experience with Power BI, Tableau, or similar visualization tools.
- Previous experience working with international or US-based clients.

## Salary & Benefits

- Starting Salary: PKR 200,000+ per month
- Salary negotiable based on technical expertise and experience.
- 100% remote working opportunity.
- Opportunity to work on USA-based projects.
- Exposure to advanced AI and machine learning technologies.
- Professional growth and career development opportunities.
- Collaborative international working environment.
- Long-term career opportunities.

## Ideal Candidate

We are looking for someone who:

- Has practical experience developing and deploying AI solutions.
- Can independently manage technical assignments.
- Understands real-world AI and data science applications.
- Has strong communication and technical problem-solving skills.
- Can work effectively with international clients.
- Is passionate about AI innovation and emerging technologies.

## How to Apply

Interested candidates are encouraged to apply with their updated CV and relevant AI/Data Science project portfolio.

Join Crystal Techify and work on innovative AI projects while building your career in the international technology industry.

In this role, you will lead a dedicated red-teaming team, building and running an independent program that actively probes Apple Intelligence features for safety and security risks, while upholding Apple's values, privacy, and quality standards.

## Description

We are seeking a visionary Machine Learning Engineering Leader to build, mentor, and develop a high-performing team driving Responsible AI efforts for global generative AI products. In this highly cross-functional role, you will partner with leadership, design, engineering, legal, and regulatory teams to define robust safety policies that align with product goals. You will provide critical technical direction for dataset design and safety alignment strategies, while directly overseeing the implementation of end-to-end mitigation architectures in production. Pre and Post-launch, you will remain hands-on in analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a champion for your team, you will foster an inclusive culture of technical excellence, empower senior leadership with safety recommendations, and systematically remove roadblocks to ensure team success.

## Minimum Qualifications

- 5+ years of experience in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision, with 2+ years directly managing engineering teams
- Proven track record of leading technical teams through ambiguity to deliver high-quality, high-impact results.
- Proficiency in Python and data science libraries (e.g. Pandas) with strong skills in data analysis, visualization, and applied ML workflows
- Excellent communication skills and proven ability to translate complex technical insights for cross-functional partners, senior leadership, and executives
- Strong analytical and independent problem-solving skills, with ability to guide teams through ambiguity
- Familiarity interpreting outputs from human and automated evaluations, particularly with complex, nuanced, or multi-labeled data, to inform mitigation improvements and shipping decisions
- Experience collecting and analyzing language, vision, or multimodal datasets
- Background in failure analysis, quality engineering, or robustness testing for ML-driven systems
- Comfortable leading a team that works with sensitive or potentially offensive content

## Preferred Qualifications

- Experience working in the Responsible AI space
- Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, EMNLP, etc.)
- Experience working on Responsible AI and AI Safety
- Strong organizational and operational skills working with large, multi-functional, and diverse teams
- Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable

## Roles & responsibilities

- Develop and deploy software, AI, and data-driven solutions.
- Collaborate with business teams to understand requirements and solve operational challenges.
- Integrate applications with enterprise systems and digital platforms.
- Participate in testing, troubleshooting, and production support.
- Support implementation of Generative AI, automation, and analytics initiatives.
- Document solutions and contribute to continuous improvement efforts.

## About the Role

Cognizant is seeking high-potential graduates to join its Digital & AI team as Forward Deployment Engineers (FDEs). This role combines software engineering, AI innovation, and business problem-solving to deliver technology solutions that improve business operations and customer experience. Forward Deployment Engineers work directly with business stakeholders to turn ideas into scalable, production-ready solutions.

## Required Qualifications

- Bachelor's degree in Computer Science, Information Technology, Software Engineering, AI, Data Science, or related field.
- 0-2 years of experience (fresh graduates encouraged to apply).
- Proficiency in Python, Java, JavaScript, or similar programming languages.
- Understanding of databases, APIs, LLMs, and software development fundamentals.
- Strong analytical, problem-solving, and communication skills.
- Willingness to learn, collaborate, and work in a dynamic environment.

## Preferred Skills

- Exposure to AI/ML, Generative AI, Cloud (Azure/AWS), or Data Analytics.
- Internship, academic project, hackathon, or relevant practical experience.
- Interest in Digital Transformation, and Emerging Technologies.

## Ideal Candidate

A curious, technology-driven graduate who enjoys coding, solving business problems, and building innovative solutions that create measurable impact.

## About Cognizant

Cognizant (Nasdaq: CTSH) engineers modern businesses. We help our clients modernize technology, reimagine processes and transform experiences so they can stay ahead in our fast-changing world. Together, we're improving everyday life. See how at www.cognizant.com or @cognizant.

## Role Summary

The AI/ML Engineer is tasked with creating, implementing, and refining machine learning and generative artificial intelligence solutions. Operating at the convergence of data engineering, analytics, product strategy, and machine learning, this position focuses on constructing systems capable of aggregating, organizing, and analyzing vast quantities of African data. The primary objective is to convert this raw information into searchable intelligence, automated insights, predictive analytics, and decision-support mechanisms.

## Key Responsibilities

- Architect, engineer, and launch machine learning models tailored for business intelligence, market forecasting, classification, recommendation engines, and other strategic applications.
- Industrialize AI models that transform diverse African data sources into actionable business insights.
- Construct predictive and analytical frameworks covering sectors such as economics, financial markets, industries, corporate entities, and consumer trends.
- Assess various machine learning methodologies to select optimal models based on metrics including accuracy, scalability, cost-efficiency, and business impact.
- Track model performance metrics and iterate on algorithms to enhance accuracy as new data streams become available.
- Engineer applications leveraging Large Language Models (LLMs) and foundational models to drive innovation.
- Architect Retrieval-Augmented Generation (RAG) systems that allow AI tools to access and reason over internal datasets, research archives, and knowledge bases.
- Create AI-driven research assistants designed to search, synthesize, and interpret extensive information repositories.
- Design intelligent query interfaces specifically for African economic, industrial, and business data.
- Execute prompt engineering, structured output generation, function calling, tool integration, and agentic workflow implementation.
- Optimize LLM performance regarding latency, cost, and accuracy.
- Investigate model fine-tuning and adaptation strategies where they offer distinct advantages over standard prompting or RAG techniques.
- Collaborate on the creation of the company's proprietary African Intelligence Engine.
- Develop AI functionalities capable of interpreting African markets, economic conditions, industries, and business landscapes.
- Create structured knowledge graphs representing African nations, corporations, sectors, markets, and economic indicators.
- Integrate fragmented datasets to generate comprehensive intelligence.
- Build systems capable of detecting relationships, trends, anomalies, and emerging patterns within African data.
- Facilitate the progression of data through the value chain: from raw data to information, insight, intelligence, and finally, decision-making.
- Contribute to the evolution of proprietary AI technologies.
- Partner with data engineering teams to establish robust data pipelines for AI and ML initiatives.
- Clean, transform, and prepare both structured and unstructured data for model training and development.
- Engineer pipelines supporting model training, inference, and evaluation cycles.
- Manage interactions with APIs, databases, cloud storage, and external data providers.
- Establish protocols for data validation, quality assurance, and feature engineering.
- Define organizational standards for data readiness for AI applications.
- Engineer AI agents capable of executing complex, multi-step research and analytical workflows.
- Construct automated workflows where AI independently retrieves data, analyzes information, generates outputs, and initiates downstream actions.
- Integrate AI models with internal databases, APIs, analytical tools, and legacy software systems.
- Implement human-in-the-loop verification processes where expert judgment is necessary.
- Identify repetitive research and analytical tasks suitable for AI automation.
- Deploy AI and machine learning models into live production environments.
- Implement processes for model monitoring, version control, testing, and evaluation.
- Track model reliability, latency, and inference costs to ensure operational efficiency.
- Guarantee that AI applications maintain scalability and reliability as user demand grows.
- Collaborate with product, research, analytics, and business units to translate business challenges into AI-driven solutions.
- Rapidly prototype AI-enhanced products and features.
- Scale successful prototypes into robust production applications.
- Engage in product discovery, experimentation, and user testing phases.
- Identify avenues for creating new revenue streams through AI-powered products and services.
- Assist in the development of APIs and AI service offerings.
- Stay current with advancements in AI, machine learning, generative AI, LLMs, and AI agents.
- Evaluate emerging models, frameworks, and tools to assess their strategic relevance.
- Conduct experiments and proof-of-concept projects to validate new technologies.
- Enrich the company's technical knowledge base and AI research library.
- Prioritize the development of proprietary capabilities over exclusive reliance on third-party AI platforms.

## Required Qualifications

- Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Mathematics, Statistics, Data Science, Electrical/Electronic Engineering, or a related quantitative field.
- 1-2 years of professional experience in AI/ML, machine learning engineering, data science, or a comparable technology domain.
- Proficient programming abilities in Python.
- Demonstrated hands-on experience in developing and deploying machine learning models.
- Familiarity with contemporary AI/ML frameworks and libraries.
- Experience working with APIs, databases, and data pipeline architectures.
- Proficiency with at least one major cloud computing platform, such as AWS, Azure, or Google Cloud.
- Solid grasp of software engineering principles and Git-based version control workflows.

TriMark Digital is seeking an AI Product & Automation Specialist to help build AI-powered tools, agents and workflows that improve how our team works and expand the solutions we offer clients. This role will turn business challenges into practical applications, from internal assistants and process automations to prototypes for new products and services.

The ideal candidate is a curious, resourceful builder who actively explores AI and has already used it to create something useful. You enjoy figuring out how things work, connecting tools and improving an idea through experimentation and feedback.

This is an early-career opportunity focused on initiative, problem-solving and demonstrated ability. A traditional web development background is not required. Your experience may come from internships, coursework, personal projects or independent learning.

## AI Product & Agent Development

- Build AI-powered tools, agents and applications that address internal and client needs.
- Translate ideas and business requirements into working prototypes.
- Use AI-assisted development tools, agent builders and no-code or low-code platforms to create functional solutions.
- Refine prototypes based on feedback and collaborate with developers when projects require additional technical support.

## Workflow Automation & Integration

- Identify opportunities to reduce repetitive tasks and improve how information moves between teams and systems.
- Build workflows that connect tools, organize information and support marketing, sales and agency operations.
- Explore APIs and integrations to extend functionality and connect existing platforms.
- Troubleshoot issues and maintain automations as needs evolve.

## Research & Experimentation

- Explore emerging AI tools and evaluate their potential for specific business applications.
- Test different approaches and recommend tools based on usefulness, reliability and ease of adoption.
- Share findings and demonstrate practical applications to the broader team.
- Contribute ideas for new AI-powered products and services.

## Testing & Continuous Improvement

- Test tools for accuracy, usability and reliability before broader use.
- Identify errors, limitations and situations that require human review.
- Gather user feedback and improve functionality over time.
- Document how tools work, how to use them and what their limitations are.

## Collaboration & Business Application

- Work with strategists, creatives, developers and other team members to understand challenges and define useful solutions.
- Explain technical concepts clearly to colleagues with varying levels of AI experience.
- Help teams adopt new tools and incorporate them into their daily work.
- Connect projects to clear objectives, such as saving time, improving the customer experience or supporting sales and marketing.

## Requirements

- Hands-on experience using AI to build agents, applications, automations or other functional tools.
- Examples of completed or working projects that demonstrate initiative and problem-solving. Personal projects, coursework and independent experiments are welcome.
- Familiarity with AI-assisted development, agent-building or workflow automation platforms, with a willingness to learn new tools.
- An interest in APIs, integrations and how systems exchange information.
- Ability to research, troubleshoot and work through unfamiliar challenges.
- Strong attention to detail and a willingness to test and question AI-generated outputs.
- Clear communication skills and the ability to collaborate across disciplines.
- Strong organizational skills and follow-through, including documenting and improving what you build.
- An interest in applying AI to marketing, customer experiences and business operations.
- A computer science degree or traditional web development background is not required. Familiarity with reading or adapting code is helpful.

When applying, please include two or three examples of something you’ve built using AI. Links, short demonstrations or project walkthroughs are welcome. Tell us what problem you were solving, which tools you used, what you personally contributed and what you learned.

The application window is expected to close on: 11/22/2026

## Meet the Team

The Cisco IT AI Infrastructure team delivers high-performance compute (HPC) and accelerated AI infrastructure as a service across Cisco's global enterprise footprint. We provide foundational supercomputing platforms that empower engineering, research, security, and product teams. Our organization architects, builds, and operates the enterprise-grade supercomputing infrastructure that powers Cisco's foundational models, distributed AI training, inference engines, and machine learning platforms.

## Your Impact

As an AI Infrastructure Technical System Engineer and Technical Leader, you will serve as the principal systems architect and technical authority for our enterprise AI platforms. You will establish architectural direction, spearhead complex infrastructure initiatives, mentor engineering talent, and bridge accelerated hardware capabilities with high-performance software execution.

You will collaborate with a global multi-disciplinary team, interfacing regularly with internal AI Researchers, Cisco Hardware & Network Architecture Teams, and Industry Ecosystem Partners (NVIDIA, AMD, Red Hat) to engineer and operate a cutting-edge, large-scale AI technology stack.

## Architecture, Strategy & Capacity Engineering

- Lead the architectural design, hardware qualification, capacity planning, and maintenance of large-scale bare-metal GPU clusters (NVIDIA/AMD).
- Architect resilient, multi-tenant compute and control planes across bare-metal Kubernetes, enterprise container platforms (Red Hat OpenShift), and HPC cluster managers (NVIDIA BCM).
- Collaborate with network engineering to design, benchmark, and optimize high-throughput, low-latency backend fabrics (RDMA, RoCEv2, 400G/800G).

## Infrastructure as Code (IaC), GitOps & SRE Automation

- Champion Site Reliability Engineering to eliminate operational toil, drive autonomous self-healing, and uphold stringent Service Level Objectives (SLOs).
- Architect IaC and GitOps deployment pipelines using Ansible, Terraform, Python, Go, and modern CI/CD tooling.
- Oversee automated workflows for firmware baselines, BIOS/BMC configuration, kernel driver updates, platform upgrades, and certificate rotations.

## AI Workload Orchestration & Systems Performance

- Optimize distributed workload scheduling, fair-share queueing, and GPU quota governance across frameworks (Slurm, Kueue, Volcano, Ray).
- Profile low-level systems performance, diagnosing device interconnect bottlenecks, bandwidth utilization, memory hierarchies, and compute efficiency.
- Establish automated Day-2 diagnostics and recovery procedures for GPU degradation, driver anomalies, and hardware faults.

## Observability, Governance & Technical Leadership

- Architect end-to-end observability standards using OpenTelemetry (OTel), Prometheus, and Splunk to deliver role-specific visualization dashboards and anomaly detectors.
- Serve as the senior escalation authority for high-impact incidents, leading root-cause analyses (RCAs) and aligning operations with ITIL frameworks.
- Author architecture blueprints and standard operating procedures (SOPs); mentor and coach mid-level and senior engineers to foster a culture of innovation.

## Minimum Qualifications

- Bachelor's degree in Computer Science, Engineering, IT, or related discipline with 5+ years of progressive experience in enterprise systems engineering, HPC, AI infrastructure, or SRE.
- Proficiency in Python, Go, or Bash, with extensive experience building declarative automation (Ansible, Terraform, CI/CD, GitOps).
- Advanced expertise designing and administering production Kubernetes, Red Hat OpenShift, and HPC workload managers (Slurm, Kueue, Volcano, Ray).
- Strong hands-on understanding of AI backend network fabrics, RDMA technologies (RoCEv2), and high-speed multi-hundred-gigabit network topologies.
- In-depth knowledge of enterprise Linux (RHEL/Ubuntu), kernel module lifecycle, memory subsystems, GPU device drivers, and out-of-band management (Redfish, IPMI).

## Preferred Qualifications

- Master's degree in Computer Science, Computer Engineering, or a related technical discipline (or an additional 2+ years of equivalent specialized engineering experience).
- 3+ years of experience managing enterprise server platforms at scale (e.g., environments with 500+ nodes), including automated hardware provisioning and centralized infrastructure management solutions.
- 2+ years of hands-on experience deploying, troubleshooting, and optimizing heterogeneous GPU software stacks (e.g., NVIDIA CUDA, AMD ROCm) and executing GPU validation suites in production environments.
- 3+ years of experience designing and implementing enterprise secrets management architectures (e.g., HashiCorp Vault) and integrating identity federation protocols (OIDC, SAML, SSO) across multiple production applications.
- Possession of at least one active, current industry-recognized advanced certification (e.g., CKA/CKS, RHCA/RHCE, or advanced networking credentials).
- Demonstrable record of active contributions (e.g., verifiable authored commits, merged pull requests, or published technical documentation) to open-source infrastructure projects, Kubernetes SIGs, HPC scheduling communities, or telemetry frameworks.

## Why Cisco?

At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

## Message to applicants applying to work in the U.S. and/or Canada

The starting salary range posted for this position is $140,300.00 to $178,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco's policies:

- 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
- 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
- Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
- Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
- 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
- Additional paid time away may be requested to deal with critical or emergency issues for family members
- Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

- .75% of incentive target for each 1% of revenue attainment up to 50% of quota;
- 1.5% of incentive target for each 1% of attainment between 50% and 75%;
- 1% of incentive target for each 1% of attainment between 75% and 100%; and
- Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area: $168,300.00 - $247,000.00

Non-Metro New York state & Washington state: $150,200.00 - $218,400.00

- For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.
- Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.