Job description
Role: AI Engineer

Experience:

5+ Years

Location:

Any Xebia Office

Skills required:

Azure Generative AI & Azure AI Foundry (Mandatory)

Retrieval-Augmented Generation (RAG) (Mandatory)

AI Agents & multi-agent orchestration (Mandatory)

Data Science & AI solution design (Mandatory)

Python (Mandatory)

Power Apps integration (Good To Have)

Copilot Studio and open-source AI platforms (Good To Have)
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Qualifications

• The ideal candidate is comfortable creating agent applications that showcase what is possible, is curious about and experienced with open-source models, and enjoys turning them into reliable, high-impact features

• 3+ years of experience in software engineering, preferably in backend, ML systems, or API development

• Bachelor’s or Master's degree in Computer Science, Computer Engineering, or equivalent

• Strong programming skills in Python; experience with various Python frameworks

• Solid understanding of LLM workflows, agent patterns, or tool invocation systems

• Experience designing and delivering production APIs

• Familiarity with open-source LLMs and multimodal models (HuggingFace, LangChain, LlamaIndex, etc.)

• Strong foundations in cloud-native development

• 5 more items(s)

Benefits

• Flexible working hours

• Daily lunch and dinner provided; unlimited snacks and beverages

• Supportive and highly collaborative work environment

• Health check-up support and top-tier equipment/hardware support

• A front-row seat to the generative AI infrastructure revolution

• Competitive compensation, startup equity, health insurance, and other benefits

• 3 more items(s)

Responsibilities

• We’re seeking an Agent Engineer to design and build agentic features in our platform, including document understanding, advanced RAG, and customer support automation

• In this role, you will develop not only the agent components themselves, but also the Friendli Agent API, which serves as the core developer interface for building and extending agent applications

• You will also build agent applications as production-ready examples of how agents can solve real-world problems

• These applications will be primarily written in Python and will serve as reference implementations for our customers and community

• Design, build, and maintain agent APIs and applications that deliver document understanding and other high-value features

• Evaluate and integrate open-source models to power production-ready agent features where possible

• Develop reference agent applications to showcase workflows and accelerate customer adoption

• Collaborate with backend and infrastructure teams to integrate agents with deployment, orchestration, and monitoring systems

• Ensure APIs are robust, developer-friendly, and enterprise-ready through strong design principles and documentation

• Continuously improve the reliability, scalability, and performance of agent features in production

• 7 more items(s)

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Job description

About the Job

We’re seeking an Agent Engineer to design and build agentic features in our platform, including document understanding, advanced RAG, and customer support automation. In this role, you will develop not only the agent components themselves, but also the Friendli Agent API, which serves as the core developer interface for building and extending agent applications. You will also build ...agent applications as production-ready examples of how agents can solve real-world problems.

These applications will be primarily written in Python and will serve as reference implementations for our customers and community. We are looking for a hands-on engineer who is passionate about building agent systems and making AI easy for developers to adopt. The ideal candidate is comfortable creating agent applications that showcase what is possible, is curious about and experienced with open-source models, and enjoys turning them into reliable, high-impact features.

Key Responsibilities

• Design, build, and maintain agent APIs and applications that deliver document understanding and other high-value features

• Evaluate and integrate open-source models to power production-ready agent features where possible

• Develop reference agent applications to showcase workflows and accelerate customer adoption

• Collaborate with backend and infrastructure teams to integrate agents with deployment, orchestration, and monitoring systems

• Ensure APIs are robust, developer-friendly, and enterprise-ready through strong design principles and documentation

• Continuously improve the reliability, scalability, and performance of agent features in production

Qualifications

• 3+ years of experience in software engineering, preferably in backend, ML systems, or API development

• Bachelor’s or Master's degree in Computer Science, Computer Engineering, or equivalent

• Strong programming skills in Python; experience with various Python frameworks

• Solid understanding of LLM workflows, agent patterns, or tool invocation systems

• Experience designing and delivering production APIs

• Familiarity with open-source LLMs and multimodal models (HuggingFace, LangChain, LlamaIndex, etc.)

• Strong foundations in cloud-native development

Preferred Experience

• Experience with document understanding pipelines (e.g., OCR, RAG, summarization, structured extraction)

• Familiarity with Kubernetes or container orchestration in production

• Built or contributed to agent frameworks, SDKs, or CLIs

• Have worked in a startup or fast-paced environments with ownership and ambiguity

• Passion for developer experience and enabling AI adoption

Benefits

• Flexible working hours

• Daily lunch and dinner provided; unlimited snacks and beverages

• Supportive and highly collaborative work environment

• Health check-up support and top-tier equipment/hardware support

• A front-row seat to the generative AI infrastructure revolution

• Competitive compensation, startup equity, health insurance, and other benefits.

About FriendliAI

FriendliAI is building the world’s best AI inference platform that makes large language and multi-modal models fast, efficient, and deployable at scale. We power high-throughput, low-latency AI workloads for organizations worldwide and integrate directly with Hugging Face, giving developers instant access to over 500,000 open-source models.

We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference engine, we are building a platform that the AI industry can actually rely on.

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Job description

Lead Engineer (AI) / Product Technical Lead

Full-Time | On-Site / Hybrid | Islamabad, Pakistan | 1 Open Position

ABOUT THE COMPANY

Veyn.ai is redefining customer experience through Conversational AI and Generative AI. Our platform powers intelligent automation and agentic AI capabilities that enable businesses to engage customers proactively, operate efficiently, and scale beyond what tradition...al solutions allow. We build for outcomes — setting new industry benchmarks and unlocking growth for the enterprises we serve.

ROLE OVERVIEW

We are looking for an experienced and technically strong Product Technical Lead / Lead Engineer (AI) to drive the architecture, development, and delivery of AI-powered products across Generative AI, Speech AI, NLP, and Computer Vision domains. This is a senior leadership role that sits at the intersection of hands-on engineering and technical strategy. You will lead a team of AI engineers, define the technical roadmap, and work closely with cross-functional teams and stakeholders to bring intelligent systems to production at scale.

REPORTING STRUCTURE

Reports directly to the Chief Technical Officer (CTO).

The AI Engineer reports into this role.

KEY RESPONSIBILITIES

• Lead, mentor, and grow a team of AI engineers working across Generative AI, Speech AI, NLP, and Computer Vision domains.

• Architect and oversee the development of AI software applications and end-to-end AI pipelines from concept to production.

• Design and implement NLP modules covering text understanding, speech analysis, and knowledge representation.

• Build and maintain computer vision systems including object detection, tracking, recognition, and crowd analytics.

• Optimize and deploy AI pipelines and deep learning models for scalable cloud servers as well as edge and embedded platforms.

• Define and own the technical roadmap for AI products; oversee the full AI product development lifecycle.

• Drive GPU load balancing strategies and apply ML optimization techniques to maximize performance and efficiency.

• Collaborate cross-functionally with software development teams and communicate technical direction clearly to diverse stakeholders.

REQUIRED QUALIFICATIONS

Education: Bachelor's degree (BS/BE) in Computer Science, Software Engineering, Electrical Engineering, or a related discipline from a reputable institution.

Experience: 5 to 8 years of hands-on experience in AI/ML engineering, with a minimum of 2 years in a technical lead or engineering management capacity.

REQUIRED SKILLS & EXPERTISE

AI & Machine Learning

• Strong foundational knowledge of Machine Learning and Deep Learning principles, architectures, and workflows.

• Hands-on experience leading the design and development of AI systems and engineering teams.

Large Language Models (LLMs) & Generative AI

• Proficiency with LLMs, LLM hosting frameworks, and developer APIs including OpenAI API, Anthropic Claude, Google Gemini, Mistral, Meta LLaMA, and LangChain.

Natural Language Processing (NLP) & Speech AI

• Strong background in NLP with working familiarity with libraries such as spaCy and NLTK

• Solid understanding of speech processing fundamentals. With a Hands-on experience in Speech AI models and Libraries like, Whisper, Wav2wec, Librosa, Pydub, TorchAudio etc

Computer Vision

• Strong background in Computer Vision with working familiarity with OpenCV and GStreamer.

ML Optimization & Deployment

• Experience with GPU load balancing and ML optimization libraries including deep stream, TensorRT and vLLM.

Backend & API Development

• Hands-on experience in backend and API development, preferably with FastAPI, Django, Flask, or gRPC.

Databases

• Hands-on experience with relational, document, and vector databases, preferably PostgreSQL, MongoDB, Elasticsearch, and Qdrant.

Infrastructure & Cloud

• Familiarity with containerized deployments using Docker.

• Experience with cloud deployment on AWS or Google Cloud Platform (GCP).

NICE TO HAVE

• Published research papers or patent experience in AI/ML-related domains.

THE TECH STACK

LLMs & Generative AI

• OpenAI API, Anthropic Claude, Google Gemini, Meta LLaMA, LangChain, vLLM

AI & ML Optimization libraries

• CUDA/cuDNN, TensorRT, vLLM, Triton, GPU load balancing and performance optimization

Computer Vision, NLP & Speech AI

• OpenCV, GStreamer, spaCy, NLTK, Librosa, Pydub, TorchAudio etc

Backend & Infrastructure

• FastAPI, Django, Flask, gRPC, Docker, AWS, GCP

Databases

• PostgreSQL, MongoDB, Elasticsearch, Qdrant (Vector DB)

COMPENSATION & BENEFITS

Salary: Market competitive, commensurate with experience.

Benefits:

• Fuel Allowance

• Health Insurance

• Leave Encashment

• Paid Leaves

WHY JOIN US

We build, publish, and ship. Our team spans PhD researchers, engineers who patent, and PMs who close enterprise deals. The tech is real, the problems are hard, and the people around you will make you sharper. Veyn.ai is where serious AI careers are built.

HOW TO APPLY

Apply directly through LinkedIn. We look forward to hearing from you.

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Job description

A pioneering AI infrastructure company is seeking a Research Scientist specializing in LLM pretraining. This remote, full-time role involves tackling challenging problems in AI while leveraging decentralized technology. The ideal candidate will have expertise in LLM research and proficiency in PyTorch. As part of the team, you will play a crucial role in shaping next-gen language model training. T...his position offers equity and token allocation as part of the compensation package.

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Job description

Preferred Major: Bachelor's degree in Computer Science or equivalent

Experience Required:

At least 3 years of experience in the same field

Minimum Job Requirements:

• Cloud Skills - GCP/OpenShift, Kubernetes (k8s), Docker containers/images

• AI Skills – Model training, testing/evaluation, deployment

• ML/LLMOPs

• LLMs and GenAI core skills – how do LLMs work under the hood, inference mechan...ics of LLMs/ GenAI

• Inference scaling, distributed computing, inference benchmarking, inference planning for meeting SLAs/SLOs

• GPUs and how to work with them, distributed workloads handling, autoscaling

• NVIDIA NIMs, Huggingface

• NVIDIA Superpods (HPC, slurm, k8s)

• Monitoring, dashboards for LLM/ML workloads and applications

• AI Application Architecture know-how, end to end flows

• DevOps (CI/CD, argoCD, git, Jenkins etc)

• Languages: Python, SQL

Skills

Professionalism of communications and soft skills, good leadership in project management

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The Position

We're seeking an AI specialist to join our multidisciplinary team in developing cutting-edge AI solutions for education. The role focuses on fine-tuning and implementing AI models that enhance learning and teaching effectiveness through our educational platforms.

Key Responsibilities:

• AI Solution Design: Conceptualize and develop innovative AI solutions tailored for educational ap...plications, enhancing learning and teaching experiences.

• LLM Fine-Tuning: Customize and fine-tune Large Language Models to address specific educational use cases, ensuring relevance and effectiveness.

• RAG & Knowledge Systems: Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured educational content to improve factual accuracy and contextual relevance.

• Agentic AI Systems: Design, implement, and evaluate AI agent–based architectures (multi-agent systems, tool-using agents, autonomous workflows) for complex educational tasks.

• Model Context & Tool Integration: Implement and manage Model Context Protocol (MCP)–based integrations to enable secure, scalable, and standardized access to tools, data sources, and services for LLM-powered systems.

• AI Pipeline Development: Create and optimize robust AI pipelines for processing, retrieval, orchestration, and analysis of educational data, ensuring efficiency and scalability.

• ML Infrastructure Management: Build, deploy, and maintain scalable machine learning infrastructure to support ongoing and future AI initiatives.

• Collaborative Research: Work closely with the research team to analyze data on learning effectiveness, leveraging insights to inform AI development.

• Technical Documentation: Document detailed technical specifications, algorithms, architectures, and workflows, and maintain a clean, organized codebase.

• Continuous Improvement: Stay updated with advancements in LLMs, agentic frameworks, MCP standards, and EdTech research, integrating new methodologies into production systems.

• Cross-Functional Collaboration: Partner with product managers, educators, and other stakeholders to align AI initiatives with educational goals and user needs.

Technical Requirements:

Education:

• Master's or doctorate degree in Computer Science, AI, or related field from top universities

Essential Technical Skills:

• Machine Learning & LLM Expertise: Proven experience in ML model development, deployment, and extensive hands-on experience with Large Language Model (LLM) fine-tuning.

• RAG Implementation: Strong experience building and evaluating Retrieval-Augmented Generation systems, including embedding strategies, vector databases, chunking, reranking, and retrieval optimization.

• Agentic Framework Familiarity: Practical experience or strong familiarity with AI agentic frameworks (e.g., LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar), including tool orchestration, memory, and multi-step reasoning workflows.

• MCP Familiarity: Experience or working knowledge of Model Context Protocol (MCP) for standardized LLM access to external tools, services, and data sources.

• Programming Proficiency: Advanced skills in Python, including writing efficient, maintainable, and well-documented code.

• ML Frameworks: Proficiency with frameworks such as PyTorch and TensorFlow, with experience deploying and scaling ML models.

• Data & Storage: Strong knowledge of SQL and NoSQL databases, vector databases, and data pipelines for AI-driven applications.

• Version Control: Proficient in Git for collaborative software development.

• API Development: Experience building RESTful APIs for integrating AI services into production systems.

• Containerization: Knowledge of Docker for reproducible development and production environments.

• Cloud Computing: Understanding of cloud platforms and services supporting AI and ML workloads (if applicable).

Desired Skills:

• EdTech Industry Experience: Previous experience working within the educational technology sector, understanding its unique challenges and opportunities.

• Cloud Service Proficiency: Hands-on experience with major cloud service providers such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.

• CI/CD Pipeline Management: Experience in setting up and managing Continuous Integration and Continuous Deployment pipelines to streamline development processes.

• Evaluation & Safety: Familiarity with LLM evaluation, hallucination mitigation, guardrails, and responsible AI practices.

• Analytical Thinking: Strong analytical and problem-solving skills, with the ability to approach complex challenges methodically.

• Communication Skills: Excellent written and verbal communication abilities, capable of articulating complex technical concepts to diverse audiences.

• Project Management: Proven experience in managing projects, ensuring timely delivery and adherence to quality standards.

• Agile Methodologies: Familiarity with Agile development environments, including experience working in Scrum or Kanban frameworks.

• Team Collaboration: Ability to work effectively within multidisciplinary teams, fostering a collaborative and productive work environment.

• Innovation and Creativity: Demonstrated ability to think creatively and innovate within the AI and EdTech domains.

What We Offer:

• Competitive salary package, with an option plan for key team members

• Professional development opportunities

• Flexible working arrangements

• Collaborative and innovative work environment

• Opportunity to make meaningful impact in education

Job Type: Full-time

Pay: $30,000.00 - $50,000.00 per month

Benefits:

• Additional leave

• Employee discount

• Medical Insurance

• Opportunities for promotion

• Paid sick time

• Professional development

Work Location: In person

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Job description

A technology-driven company in the United Arab Emirates is seeking a Web Crawling & AI Lead Qualification Engineer to build a sophisticated application that identifies potential business leads. The successful candidate will develop a web crawling and AI-powered tool, design a scoring mechanism for lead qualification, and produce a handover-ready application. Strong expertise in web scraping, AI in...tegration, and software development are essential. Flexible work hours and a collaborative team culture are part of the offering.

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About The Job

At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models.

We’re focused on the security of AI systems themselves, examining how modern models can be attacked, misused, or pushed beyond their intended boundaries. You will work with realistic scenarios to help ensure AI systems remain safe, reliable, and aligned with securi...ty best practices.

Organization: Alignerr Position: AI / Emerging Tech Security Analyst Type: Contract / Task-Based Compensation: $40–$60 /hour Location: Remote Commitment: 10–40 hours/week

What You’ll Do

• Analyze AI and LLM security scenarios to understand how models behave under adversarial or unexpected conditions

• Review prompt injection, data leakage, model abuse, and system misuse cases

• Classify security issues and appropriate mitigations based on real-world impact and likelihood

• Help evaluate and improve AI system behavior so it remains safe, reliable, and aligned with security best practices

What We’re Looking For

• Background in security with a strong interest in how AI systems are built and deployed

• Understanding of modern security threat modeling applied to emerging AI technologies

• Curious, analytical, and precise when evaluating complex systems and potential risks

Why Join Us

• Competitive pay and flexible remote work.

• Work directly on frontier AI systems.

• Freelance perks: autonomy, flexibility, and global collaboration.

• Potential for contract extension.

Application Process (Takes 10–15 min)

• Submit your resume

• Complete a short screening

• Project matching and onboarding

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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Qualifications

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing

• You want to work on problems that will help change banking for good

• You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity

• You have the courage to share new ideas even when they are unproven

• You are deeply Technical

• You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies

• At least 8 years of experience programming with Python, Go, Scala, or Java

• AWS, Google Cloud, Azure, or equivalent private cloud)

• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems

• Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level

• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

• 13 more items(s)

Benefits

• Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked

• McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer

• Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter

• This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

• Incentives could be discretionary or non discretionary depending on the plan

• Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

• 3 more items(s)

Responsibilities

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production

• You adapt quickly and thrive on bringing clarity to big, undefined problems

• 4 more items(s)

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Job description

Distinguished AI Engineer

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at ...the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

• You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies

• At least 8 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

• 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems

• Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level

• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $269,100 - $307,200 for Distinguished AI Engineer

New York, NY: $293,600 - $335,100 for Distinguished AI Engineer

Richmond, VA: $244,700 - $279,200 for Distinguished AI Engineer

San Francisco, CA: $293,600 - $335,100 for Distinguished AI Engineer

San Jose, CA: $293,600 - $335,100 for Distinguished AI Engineer

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.

No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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Job description

University: United Arab Emirates University Country: United Arab Emirates Deadline: 2026-01-08 Fields: Mechanical Engineering, Electrical Engineering, Computer Engineering, Energy Systems, Artificial Intelligence Topic: UAE – Postdoc in AI & Smart Aquaculture at UAE University Fields: Mechanical Engineering, Electrical Engineering, Computer Engineering, Energy Systems, Artificial Intelligence Posi...tion: postdoc Country: asia Deadline: 2026-01-08 University: United Arab Emirates University Real Country: United Arab Emirates Main Category: engineering --- Are you passionate about leveraging artificial intelligence and digital technologies to address critical challenges in sustainable food production and renewable energy? If you are seeking to accelerate your research career while making a tangible difference in the future of aquaculture and smart systems, this postdoctoral opportunity at United Arab Emirates University could be your ideal next step. About the University or Research Institute United Arab Emirates University (UAEU), located in the vibrant city of Al Ain, is the nation’s first and foremost comprehensive university. Established in 1976, UAEU has steadily built a reputation for academic excellence, research innovation, and global collaboration. It is recognized as one of the leading research-intensive universities in the Middle East, consistently ranked among the top institutions in the Arab world. UAEU’s Department of Mechanical and Aerospace Engineering is at the...

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Qualifications

• Partner with Product teams to mature AI model efficiency benchmarks and selection criteria prioritizing environmental performance

• Lead the design and implementation of internal environmental telemetry and automated tracking tools aligned to standards and measurement frameworks for AI usage transparency

• 6+ years of experience in technical product management, software engineering, AI implementation, or data center infrastructure

• You have a passion for sustainability and are eager to apply your technical skills to decarbonizing AI and data centers

• Understanding of AI technologies, model development, LLM architectures, and operational deployment in enterprise cloud environments

• Familiarity with AI model efficiency/optimization techniques and agentic frameworks

• Ability to perform data analysis to translate raw system telemetry into actionable business strategies and sustainability KPIs

• Strong business communication skills focused on taking complex topics and making them understandable to a variety of audiences

• 5 more items(s)

Responsibilities

• In this cross-functional role, you will shape and operationalize how we manage AI energy demand and optimize resource efficiency across the AI value chain

• By partnering closely with Product, Infrastructure, Procurement, and Ethical & Humane Use teams, you will ensure that our AI technologies are built and deployed to minimize environmental impact while maximizing business value

• Collaborate with Engineering and Infrastructure teams to optimize compute power utilization and minimize energy consumption across data center infrastructure

• Work with Infrastructure to implement energy-efficient data center operations and cooling optimization for AI workloads

• Partner with hyperscaler providers to leverage geo-aware routing and clean energy availability for compute placement

• Drive "right-sizing" AI models and token usage to optimize computational demand across Agentforce and AI platform services

• Develop and drive accountability towards comprehensive AI and infrastructure sustainability KPIs tied to sustainability targets, working across cross-functional team

• Lead internal alignment initiatives with AI Research, Legal, and Business units to embed sustainability into AI development lifecycle

• Partner with Procurement to establish sustainability requirements for AI model providers and ensure supply chain transparency and data acquisition

• Collaborate with relevant teams on clean energy procurement, AI and infrastructure-related sustainability risks

• Support Salesforce in influencing the development of global sustainable AI standards

• Collaborate on customer advisory programs and sustainability roundtables, leveraging Salesforce's position as a trusted AI sustainability partner

• 9 more items(s)

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Job description

Building on the foundation laid out in Salesforce’s AI Sustainability Outlook, this role will drive innovation, operational excellence, and industry leadership in sustainable AI practices while accelerating progress towards Salesforce’s global sustainability goals.

As the Senior Manager of AI Sustainability, you will serve as the technical anchor for the Salesforce Impact team, bridging the gap b...etween our corporate sustainability targets and our rapidly evolving AI strategy. In this cross-functional role, you will shape and operationalize how we manage AI energy demand and optimize resource efficiency across the AI value chain. By partnering closely with Product, Infrastructure, Procurement, and Ethical & Humane Use teams, you will ensure that our AI technologies are built and deployed to minimize environmental impact while maximizing business value.

Key Responsibilities:

Smart Demand:

• Partner with Product teams to mature AI model efficiency benchmarks and selection criteria prioritizing environmental performance

• Lead the design and implementation of internal environmental telemetry and automated tracking tools aligned to standards and measurement frameworks for AI usage transparency

Efficiency Optimization:

• Collaborate with Engineering and Infrastructure teams to optimize compute power utilization and minimize energy consumption across data center infrastructure

• Work with Infrastructure to implement energy-efficient data center operations and cooling optimization for AI workloads

• Partner with hyperscaler providers to leverage geo-aware routing and clean energy availability for compute placement

• Drive "right-sizing" AI models and token usage to optimize computational demand across Agentforce and AI platform services

Cross-Functional Strategy, Implementation, & Industry Leadership:

• Develop and drive accountability towards comprehensive AI and infrastructure sustainability KPIs tied to sustainability targets, working across cross-functional team

• Lead internal alignment initiatives with AI Research, Legal, and Business units to embed sustainability into AI development lifecycle

• Partner with Procurement to establish sustainability requirements for AI model providers and ensure supply chain transparency and data acquisition

• Collaborate with relevant teams on clean energy procurement, AI and infrastructure-related sustainability risks

• Support Salesforce in influencing the development of global sustainable AI standards

• Collaborate on customer advisory programs and sustainability roundtables, leveraging Salesforce's position as a trusted AI sustainability partner

Required Qualifications:

• 6+ years of experience in technical product management, software engineering, AI implementation, or data center infrastructure

• You have a passion for sustainability and are eager to apply your technical skills to decarbonizing AI and data centers

• Understanding of AI technologies, model development, LLM architectures, and operational deployment in enterprise cloud environments

• Familiarity with AI model efficiency/optimization techniques and agentic frameworks

• Ability to perform data analysis to translate raw system telemetry into actionable business strategies and sustainability KPIs

• Strong business communication skills focused on taking complex topics and making them understandable to a variety of audiences

Preferred Qualifications:

• Ability to query and analyze data using SQL, Tableau and/or Python

• Experience with hyperscaler partnerships (AWS, GCP, Azure) and cloud infrastructure optimization

• Experience in infrastructure capacity planning, workload management, or cloud resource optimization.

• Experience in environmental assessment, carbon accounting, or sustainability measurement frameworks

• Degree in computer science, engineering, or other related field

Why Join Us?

At Salesforce, we believe in doing well by doing good. As the Senior Manager, AI Sustainability, you will shape the future of sustainable AI at scale, working with our most strategic customers and leading the industry toward responsible AI deployment. You'll have the opportunity to drive measurable environmental impact while supporting Salesforce's position as both an AI leader and sustainability pioneer.

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