Senior AI Engineer

Bristol Myers Squibb

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Seattle, WAMadison, NJPrinceton, NJCambridge Crossing, MABrisbane, CA
Salary: $151,280–$183,319 / yr
Posted: 17 days ago
Freshness: Confirmed live 2 days ago
Closes: Oct 26, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k

This role $167k

$139k most similar roles pay here $265k

This role pays less than 70% of similar roles. Most pay $162,000–$246,150 — the shaded band above. At the midpoint, this role pays about $167k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Bristol Myers Squibb

Bristol Myers Squibb is a global biopharmaceutical company committed to discovering, developing and delivering innovative medicines to patients.

Bristol Myers Squibb currently has 33 open roles on FindRole.

Listed pay typically runs $125,480–$152,049 across 33 roles with salary data.

Most-posted roles

View all roles at Bristol Myers Squibb

At a glance

TL;DR · Senior AI Engineer

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As a Senior AI Engineer on the AI Venture Studio team, you will serve as a hands-on individual contributor focused on the AI-first engineering of cloud-native applications and agentic products. You will design and build backend services using Python, FastAPI, or TypeScript/Node to integrate LLM APIs, retrieval systems, and workflow engines. Your daily work involves developing MCP-accessible services, managing infrastructure-as-code via Terraform or AWS CDK, and building robust CI/CD pipelines. You will utilize tools like LangGraph, LangSmith, and various AI coding agents to create scalable solutions for complex pharmaceutical problems involving unstructured knowledge and scientific evidence. The role requires expertise in AWS services, vector databases, and secure authentication patterns to transform multi-modal data into actionable insights across R&D, manufacturing, and commercialization functions within a fast-paced, agile development cycle.

What does a AI Engineer earn in Massachusetts?

Median $246150 from 62 postings across 4 companies.

See salary data

Skills

Python FastAPI TypeScript AWS LangGraph LangChain PydanticAI Claude Anthropic OpenAI Gemini LangSmith Terraform AWS CDK CloudFormation CI/CD

What you'll do

Build and deliver backend services using Python/FastAPI or TypeScript to integrate LLM APIs and agentic workflows.
Develop MCP-accessible tools and services to provide governed access to structured knowledge assets.
Design retrieval, memory, and context architectures using AWS-native vector, graph, and relational databases.
Build and operate agentic applications using frameworks like LangGraph and the Claude Agent SDK.
Create evaluation, testing, and observability frameworks to measure agent quality, latency, and cost.
Maintain CI/CD pipelines and infrastructure-as-code for deploying containerized, production-ready AI applications on AWS.
Translate complex business problems into technical architectures that align AI capabilities with measurable product outcomes.
Provide technical leadership through architecture reviews, code reviews, and the creation of reusable engineering standards.

What we're looking for

Bachelor’s or higher degree in Computer Science, Engineering, Science, or a related field.
5+ years of experience designing, building, and scaling software applications, cloud platforms, APIs, or distributed systems.
Strong proficiency in Python and FastAPI and/or TypeScript/Node.
Hands-on experience building and operating cloud-native applications on AWS.
Experience building agentic AI applications using frameworks such as LangGraph, LangChain, PydanticAI, Claude Agent SDK, or similar technologies.
Experience with containers, CI/CD, GitHub-based workflows, automated testing, and infrastructure-as-code like Terraform or AWS CDK.
Practical experience integrating enterprise LLM services such as Anthropic (preferred), OpenAI, Gemini, Grok, or AWS Bedrock.
Demonstrated ability to use AI coding agents and tools like Claude Code, Cursor, or GitHub Copilot to accelerate delivery.