Staff Software Engineer, Applied AI/ML Products

Job highlights Identified by Google from the original job post Qualifications • Bachelors degree in Computer Science, Engineering, Data Science, or a related field, with a minimum of 8 years of experience in software engineering, data engineering, or applied AI engineering (an equivalent combination of education and experience may be accepted) • Strong proficiency in Python is essential • Expertise in building and deploying applications utilizing LLM APIs and AI solutions in cloud environments (Azure, AWS) • Proven experience in Applied AI/ML and Prompt Engineering, Generative AI and LLM Integration, Enterprise Data Integration, API & Cloud Application Development, and Security-conscious Engineering • Hands-on experience with machine learning frameworks (PyTorch, TensorFlow, scikit-learn) • Comprehensive understanding of data engineering principles, APIs, and distributed systems • Familiarity with RAG architectures, vector databases, and semantic search is advantageous • Knowledge of AI governance, responsible AI practices, model explainability, and data classification is an asset • 5 more items(s) Benefits • Salary: $140,000 - 165,000 per year • We offer a competitive salary range of $140k - $165k along with performance bonuses and an extensive benefits package, including a 401(k) plan with matching contributions, health insurance, dental and vision coverage, paid time off, and an Employee Stock Purchase Program Responsibilities • Develop AI applications such as enterprise copilots, search assistants, document intelligence and generation tools, workflow automation agents, predictive models, decision-support tools, and reusable AI components including prompt libraries and solution patterns • Implement Retrieval-Augmented Generation (RAG) pipelines using enterprise data sources like SharePoint, data lakes, document repositories, and research systems • Construct and uphold comprehensive AI/ML pipelines, encompassing data ingestion, feature engineering, model training, evaluation, deployment, and monitoring • Integrate LLMs into business workflows utilizing APIs and platforms such as Azure OpenAI, OpenAI, Anthropic, and AWS Bedrock • Create frameworks for prompt-engineering, grounding, and evaluation to enhance accuracy, reliability, and alignment • Convert business use cases across various domains (e.g., medical affairs, regulatory, commercial, finance) into functional AI prototypes and production-ready applications • Collaborate with Data Scientists to scale models into production systems, and partner with Product Owners and SMEs to refine requirements, acceptance criteria, and success metrics • Deploy and maintain AI solutions on cloud platforms using contemporary APIs and best practices in software engineering • Implement MLOps and LLMOps functions including versioning, monitoring, logging, performance tracking, observability, and cost optimization • Establish guardrails and controls to prevent data leakage, hallucinations, and misuse • Integrate AI solutions with enterprise identity and data-security frameworks, including RBAC, Purview, and associated governance tools • Ensure all AI systems are reliable, scalable, and secure while adhering to data classification regulations, privacy obligations, and AI governance protocols • 9 more items(s) More job highlights Job description Applied AI Engineer (Python, ML) 💰 Salary: $140,000 - 165,000 per year

At LAI we are looking for a ML, AI engineer!

🛠️ Our tech stack:

AI, API, AWS, Azure, Cloud, Copilot, Databricks, GCP, Support, LLM, PyTorch, Python, RBAC, Security, SharePoint, TensorFlow, Machine-Learning

📝 Rquirements:

• Bachelors degree in Computer Science, Engineering, Data Science, or a related field, with a minimum ...of 8 years of experience in software engineering, data engineering, or applied AI engineering (an equivalent combination of education and experience may be accepted)

• Strong proficiency in Python is essential

• Expertise in building and deploying applications utilizing LLM APIs and AI solutions in cloud environments (Azure, AWS)

• Proven experience in Applied AI/ML and Prompt Engineering, Generative AI and LLM Integration, Enterprise Data Integration, API & Cloud Application Development, and Security-conscious Engineering

• Hands-on experience with machine learning frameworks (PyTorch, TensorFlow, scikit-learn)

• Comprehensive understanding of data engineering principles, APIs, and distributed systems

• Familiarity with RAG architectures, vector databases, and semantic search is advantageous

• Exposure to frameworks such as Azure OpenAI, Copilot Studio, LangChain, LlamaIndex, or similar technologies is preferred

• Familiarity with MLOps platforms (MLflow, SageMaker, Azure ML, Databricks) is desirable

• Experience in regulated or data-sensitive sectors (pharmaceutical, healthcare, finance) is preferred

• Knowledge of AI governance, responsible AI practices, model explainability, and data classification is an asset

• Experience in constructing enterprise copilots or agentic AI systems is a plus

👩‍💻👨‍💻 Your responsibilities are:

• Develop AI applications such as enterprise copilots, search assistants, document intelligence and generation tools, workflow automation agents, predictive models, decision-support tools, and reusable AI components including prompt libraries and solution patterns

• Implement Retrieval-Augmented Generation (RAG) pipelines using enterprise data sources like SharePoint, data lakes, document repositories, and research systems

• Construct and uphold comprehensive AI/ML pipelines, encompassing data ingestion, feature engineering, model training, evaluation, deployment, and monitoring

• Integrate LLMs into business workflows utilizing APIs and platforms such as Azure OpenAI, OpenAI, Anthropic, and AWS Bedrock

• Create frameworks for prompt-engineering, grounding, and evaluation to enhance accuracy, reliability, and alignment

• Convert business use cases across various domains (e.g., medical affairs, regulatory, commercial, finance) into functional AI prototypes and production-ready applications

• Collaborate with Data Scientists to scale models into production systems, and partner with Product Owners and SMEs to refine requirements, acceptance criteria, and success metrics

• Deploy and maintain AI solutions on cloud platforms using contemporary APIs and best practices in software engineering

• Implement MLOps and LLMOps functions including versioning, monitoring, logging, performance tracking, observability, and cost optimization

• Establish guardrails and controls to prevent data leakage, hallucinations, and misuse

• Integrate AI solutions with enterprise identity and data-security frameworks, including RBAC, Purview, and associated governance tools

• Ensure all AI systems are reliable, scalable, and secure while adhering to data classification regulations, privacy obligations, and AI governance protocols

View this job and over 500 other transparent jobs with salaries (💰💰💰) & tech stacks (🛠️) on DevITJobs

Category: ML, AI Developer / Engineer

Location address: 1110 Business Pkwy S, Garden-Grove, United States

Salary: $140,000 - 165,000 per year

Benefits & perks that we offer:

LAI - More about us and the role:

We are looking for an Applied AI Engineer to join our team as a full-time, direct hire.

This role will be based in the Carmel Valley area of San Diego, CA, allowing for a hybrid work environment with three days onsite each week (Tuesday, Wednesday, Thursday).

We offer a competitive salary range of $140k - $165k along with performance bonuses and an extensive benefits package, including a 401(k) plan with matching contributions, health insurance, dental and vision coverage, paid time off, and an Employee Stock Purchase Program.

In this position, you will build and deploy AI solutions that enhance various business workflows and contribute significantly to our enterprise operations.

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