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Bristol Myers Squibb

Senior AI Engineer

Bristol Myers Squibb

full time · Senior

$137,530 – $183,319

Listed on Bristol Myers Squibb’s own careers site. You apply with them directly — we never stand between you and the employer.

What this role is

This is a hands-on senior AI engineering role building cloud-native, AI-powered applications and agentic systems for pharmaceutical use cases. The position suits experienced backend engineers who are comfortable with frontier AI technologies, want to work on high-impact problems in a fast-paced delivery model, and can bridge AI capabilities with production reliability and enterprise architecture.

Our summary, not Bristol Myers Squibb’s wording. The full posting is on their site.

What they ask for

Required

  • Bachelor's degree in Computer Science, Engineering, or related field
  • 5+ years building and scaling software applications, cloud platforms, APIs, or distributed systems
  • Strong proficiency in Python/FastAPI or TypeScript/Node
  • Hands-on experience building cloud-native applications on AWS
  • Experience designing and delivering AI-powered applications with LLMs, retrieval systems, workflows, or agents
  • Experience building agentic AI applications using LangGraph, LangChain, PydanticAI, Claude Agent SDK, or similar
  • Experience with containers, CI/CD, GitHub workflows, automated testing, and infrastructure-as-code (Terraform, AWS CDK, CloudFormation)
  • Practical experience integrating enterprise LLM services (Anthropic, OpenAI, Gemini, AWS Bedrock, or similar)
  • Understanding of architectural patterns for scaling AI applications from prototype to production
  • Working knowledge of secure AI patterns: authentication, authorization, SSO, secrets management, auditability, guardrails
  • Demonstrated ability to use AI coding agents and AI-assisted development tools
  • Strong communication skills and ability to work in fast-moving, cross-functional agile teams

Nice to have

  • Experience building MCP servers, MCP tools, or FastMCP applications
  • Experience designing retrieval, memory, and knowledge architectures with vector stores, relational and graph databases
  • Experience developing multi-agent systems, workflow orchestration, tool-calling architectures, and durable execution patterns
  • Experience with evaluation-driven development, agent testing, and AI observability platforms
  • Experience with semantic layers, natural-language-to-SQL systems, or governed data access patterns
  • Experience building sandboxed execution environments and audit-friendly agent architectures
  • Experience deploying and operating production AI applications with real-world users and SLOs
  • Experience partnering on chat, copilot, citation/provenance, and streaming user experiences
  • Active GitHub contributions, open-source participation, or demonstrated AI projects
  • Experience in life sciences, pharmaceutical, healthcare, or regulated industries

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