Senior AI Platform Engineer — Cloud-Native AWS

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

Benefits offered by this job

Health Coverage

Wellbeing Programs

401(k) plan

Paid Time Off

Job summary

Bristol Myers Squibb is seeking a Senior AI Application Engineer to join the AI Venture Studio delivery team. You will build secure cloud-hosted applications, design APIs, and develop agentic AI workflows using LangGraph and FastMCP patterns on AWS.

You’ll drive six two-week sprints to deliver MVPs, address pharma-related data challenges, and ensure reliability, observability, and enterprise alignment across R&D, Commercialization, Manufacturing, and enabling functions.

Qualifications

• Bachelor's or higher in Computer Science, Engineering, Science, or related field.

Responsibilities

• Design, build, and operate backend services and APIs for AI Accelerator products.
• Develop Python/FastAPI, TypeScript/Node services integrating LLM APIs and retrieval systems.
• Execute six two-week sprints in a 12-week cycle delivering MVP increments.
• Build MCP/FastMCP read-write-search APIs with permissioned stores and version control.
• Implement secure authn/authz, SSO, secrets management, and auditability.
• Collaborate with frontend teams to define API contracts and error handling.
• Lead MVP demos, track performance, and ensure scalable delivery.

Skills

Cross-functional collaboration

Cloud-native development

AI/ML tooling

Backend API design

Python

TypeScript/Node

Security & compliance

Observability

Communication

Leadership

Education

Bachelor's degree in CS/Engineering/related

Tools

AWS

S3

RDS/PostgreSQL

OpenSearch

Redis

Fargate

Terraform

AWS CDK

LangGraph

LangSmith

FastMCP

Job description

Bristol Myers Squibb is seeking a Senior AI Application Engineer to join the AI Venture Studio delivery team. You will build secure cloud-hosted applications, design APIs, and develop agentic AI workflows using LangGraph and FastMCP patterns on AWS.

You’ll drive six two-week sprints to deliver MVPs, address pharma-related data challenges, and ensure reliability, observability, and enterprise alignment across R&D, Commercialization, Manufacturing, and enabling functions.