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Senior Manager, Full Stack Engineer, Clinical Engineering & Operations

Job in Princeton, Mercer County, New Jersey, 08543, USA
Listing for: Bristol-Myers Squibb
Full Time position
Listed on 2026-02-24
Job specializations:
  • Software Development
    AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it.

You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more:

Position Summary:

We are seeking a Senior Manager, Full Stack Engineer to serve as a technical leader in an AI‑first, agile product team supporting Global Development Operations (GDO). This role is accountable for designing, building, and operating AI‑native products where large language models, agentic workflows, and data‑driven intelligence are the default approach to solving business problems—not an add‑on.

The ideal candidate brings deep hands‑on engineering expertise and proven experience delivering production‑grade Generative and Agentic AI solutions in a regulated environment. This individual will help shape how products are designed, developed, delivered, and continuously improved, embedding AI into core workflows to augment decision‑making, automate execution, and scale impact across GDO. The role combines strong full‑stack engineering capabilities with AI product thinking
, technical roadmap ownership, and close partnership with product managers and business stakeholders to deliver measurable outcomes for patients and teams.

The role provides cross‑product technical leadership without direct line management
, influencing design decisions, shared capabilities, and long‑term technical strategy through expertise, collaboration, and hands‑on contribution.

This individual remains sufficiently hands‑on to design, build, and review critical components, while ensuring consistency, reuse, and quality across products through common patterns, reference architectures, and technical guardrails.

Specific responsibilities:
  • Accountable for the build, operation, and continuous improvement of AI‑native applications and platforms
    , including bespoke solutions and AI‑enabled SaaS, with AI as the default design paradigm.
  • Develop and maintain a strategic AI‑first technology roadmap
    , guiding build‑vs‑buy decisions, model selection, and platform capabilities in alignment with product vision and business outcomes.
  • Partner with product managers and GDO stakeholders to identify opportunities where AI can augment human decision‑making, automate execution, and create step‑change improvements in clinical and operational workflows.
  • Design, develop, and maintain scalable, stable, reliable, and secure applications using Python/Java/Node JS and modern frontend frameworks like React JS.
  • Design and operate LLM‑native and agentic systems as long‑lived products, incorporating human‑in‑the‑loop patterns, continuous learning, monitoring, and governance as part of the standard operating model. Frameworks include OpenAI, AWS Bedrock, and Lang Chain.
  • Incorporate microservices, APIs, MCPs, event‑driven processes, and middleware within enterprise systems.
  • Use critical thinking to investigate issues with systems and data, and identify solutions for short‑term remediation and long‑term strategy.
  • Develop and maintain robust ML pipelines for model training, validation, deployment, and monitoring.
  • Automate workflows, including data ingestion, feature engineering, model retraining, and versioning.
  • Implement CI/CD practices for software applications.
  • Monitor model performance in production and manage model drift, retraining, and rollback strategies.
  • Ensure compliance with data governance, privacy, and security standards.
Requirements:
  • Must have a minimum of 10 years of strong experience in…
Position Requirements
10+ Years work experience
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