AI Engineer

About

As an AI Engineer within Bristol Myers Squibb’s AI Venture Studio delivery team, you will be a hands-on individual contributor who partners with other engineers and stakeholders across the organization to build the data pipelines, integrations, and agentic AI systems that power AI Accelerator projects.

You will experiment with cutting-edge technologies through rapid prototyping, implement data-centric workflows, manage data stores, and develop multi-agent orchestration patterns using enterprise-aligned tools. Working in an agile manner with matrixed stakeholders, you will help ensure that Accelerator projects have reliable, well-engineered data foundations. Your curiosity and technical skill will directly enable 12-week project cycles to move faster by providing robust data access, transformation, and orchestration capabilities.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, build, and maintain data pipelines that feed AI Accelerator projects, including ETL workflows, data transformations, and integration with internal and external APIs and data sources.
• Develop and manage relational databases (PostgreSQL/RDS), vector databases (OpenSearch, Milvus, Amazon S3 Vectors), and knowledge graphs (Amazon Neptune, Neo4j).
• Build and operate data infrastructure on AWS, leveraging services such as S3, Athena, RDS, ElastiCache (Redis), and Fargate.

Agentic AI Development

• Build and maintain multi-agent systems using LangGraph, including state management, fan-out/fan-in orchestration, and subgraph composition.
• Develop tool integrations and MCP (Model Context Protocol) servers using FastMCP to enable agent interoperability.
• Implement LLM-powered workflows integrating foundational models (OpenAI, Anthropic, Gemini) via AWS Bedrock and direct API access.
• Build evaluation and observability pipelines using tools such as LangSmith or promptfoo.

Testing & Quality Assurance

• Write and maintain automated test suites (unit, integration, end-to-end) using pytest to ensure reliability of data pipelines and agent workflows.
• Develop evaluation frameworks for LLM outputs, including reference-based metrics and structured output validation.
• Implement data quality checks and validation at system boundaries to catch issues early in the pipeline.
• Support test-driven development practices and contribute to CI test automation.

Collaboration & Delivery

• Partner with AI Engineers, Pod Leads, and Research scientists to deliver AI Accelerator projects within 12-week cycles.
• Participate in code reviews, design discussions, and technical problem-solving with pod teams.

Qualifications & Experience

• Bachelor’s or higher degree in Computer Science, Engineering, Data Science, or a scientific field.
• 1-3 years of experience in data engineering, software engineering, or related technology or computational roles.
• Strong proficiency in Python, including data libraries (Pandas, NumPy) and web frameworks (FastAPI).
• Experience with data pipelines on AWS (S3, RDS, Athena, ElastiCache, Fargate) and relational databases (PostgreSQL), vector databases, or knowledge graphs.
• Experience with LLM application development, including prompt engineering, tool use, and structured outputs.
• Familiarity with agent frameworks (LangGraph, LangChain, PydanticAI) or demonstrated ability to learn new frameworks quickly.
• Comfort with GitHub and DevOps practices.
• Effective use of coding agents (e.g., Claude Code, Codex, Gemini CLI).
• Knowledge of and experience in agile ways of working.
• Experience writing automated tests (unit, integration, end-to-end) using pytest or similar frameworks.
• Curious and inquisitive mindset with the ability to adapt quickly to changing priorities.

#AICP If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Compensation Overview

• Cambridge Crossing: $108,650 - $131,655
• Madison - Giralda - NJ - US: $98,770 - $119,686
• Princeton - NJ - US: $98,770 - $119,686
• Seattle - WA: $108,650 - $131,655