Senior AI Platform Engineer - Cloud-Native & Agentic AI

Bristol-Myers Squibb Co; Seattle (WA); On-site; USD 151,000 - 183,000; Full time

Job summary

Bristol Myers Squibb seeks a Senior AI Application Engineer to join the AI Venture Studio delivery team, building secure cloud-hosted applications including agentic AI products and knowledge infrastructures. You will design APIs, services, and deployment pipelines that balance reliability, observability, security, and enterprise alignment.

The role follows an AI Accelerator model with six two-week sprints over 12 weeks, addressing pharma-specific problems across R&D, Commercialization, and

Qualifications

• Degree in Computer Science, Engineering, Science, or related field.
• Experience building cloud-native backend services and APIs.
• Proficiency with Python, FastAPI, and TypeScript/Node.
• Experience integrating with LLMs, retrieval systems, and workflows.
• Knowledge of security, authn/authz, and observability patterns.

Responsibilities

• Design, build, and operate backend services, APIs, and components for AI products.
• Develop MCP/FastMCP read/write/search APIs and knowledge stores.
• Implement secure patterns for auth, secrets, and auditability.
• Collaborate to define API contracts and reliable error handling.
• Lead MVP cycles with six two-week sprints in a 12-week cadence.

Skills

Python

FastAPI

TypeScript/Node

API design

Cloud engineering

Security & auth

Observability

Education

Bachelor's or higher in CS/Engineering/Science

Tools

LangGraph

LangSmith

OpenSearch

Amazon S3/Vector

PostgreSQL/RDS

Redis

AWS Fargate

Job description

Bristol Myers Squibb seeks a Senior AI Application Engineer to join the AI Venture Studio delivery team, building secure cloud-hosted applications including agentic AI products and knowledge infrastructures. You will design APIs, services, and deployment pipelines that balance reliability, observability, security, and enterprise alignment.

The role follows an AI Accelerator model with six two-week sprints over 12 weeks, addressing pharma-specific problems across R&D, Commercialization, and