AI-First Full-Stack Engineer, Clinical Ops

Bristol Myers Squibb

Princeton (NJ)

On-site

USD 94,000 - 114,000

Full time

3 days ago

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Job summary

Bristol Myers Squibb is seeking a Manager, Full Stack Engineer to join an AI‑first, agile product team supporting Global Development Operations in Princeton, NJ. You will design and operate AI‑native products where large language models and agentic workflows drive decision‑making and automation.

The ideal candidate has hands‑on engineering experience delivering production‑grade Generative/Agentic AI solutions in regulated settings, and will embed AI into core workflows across GDO to scale impact

Qualifications

Must have a minimum of 5 years of strong experience in software engineering; Pharma/Life Sciences experience is a plus.
Bachelor’s degree in Computer Science, Software Engineering, or related field.
Demonstrated track record implementing moderately complex technical solutions in a regulated environment.
Practical experience building Generative AI and Agentic AI applications using LangChain, LlamaIndex, Google ADK, etc.
Strong proficiency in Python and React; Java or TypeScript familiarity.
Solid grasp of REST APIs, MCPs, FastAPI, and JSON/XML; knowledge of TensorFlow or PyTorch.
Experience with AWS Cloud services such as Lambda, S3, DynamoDB, Bedrock, SageMaker.
Strong data analytics skills - SQL/NoSQL databases; ability to write efficient queries.
Excellent problem‑solving and analytical skills.
Ability to communicate effectively in a highly matrix organization.

Responsibilities

Design and maintain LLM‑native and agentic systems as long‑lived products with human‑in‑the‑loop patterns and governance.
Partner with product managers to identify AI opportunities to augment decision‑making and automate execution.
Design, develop, and maintain secure, scalable applications using Python/Java/Node JS/React JS.
Maintain a portfolio of SaaS and in‑house applications ensuring high availability and performance.
Collaborate with stakeholders to manage application support, incident resolution, and lifecycle activities.
Incorporate microservices, APIs, MCPs, and event‑driven processes within enterprise systems.
Investigate issues, propose short‑term fixes and long‑term strategy.
Implement CI/CD practices for software applications.
Monitor model performance in production and manage drift and retraining strategies.
Ensure data governance, privacy, and security standards.