Design, build, and maintain shared GenAI architectures, templates, and reusable components used across AI Accelerator pods.
Contribute to and apply technical standards and best practices for LLM-based applications, context engineering, MCP servers, agentic systems, and multi-modal solutions.
Develop reference implementations, starter kits, and infrastructure patterns that accelerate setup and delivery of 12-week Accelerator projects.
Continuously refine patterns and components based on feedback from pod teams, evolving needs, and advances in AI/ML services.
Pod Enablement & Delivery Support:
Partner with Pod Leads to identify where shared components and patterns can improve velocity, reliability, and consistency of delivery.
Temporarily embed with pods to help solve complex technical problems, spike new capabilities, or backfill critical skills as needed.
Provide technical coaching, design reviews, and architecture guidance to pod engineers to improve solution quality and reuse.
Assist with troubleshooting and root-cause analysis for challenging POCs or production-adjacent issues that touch shared components.
Technical Leadership & Mentorship:
Provide technical coaching through code reviews, design reviews, and architecture guidance to collaborating teams.
Communicate technical trade-offs and decisions clearly to technical peers and non-technical stakeholders.
Collaborate with stakeholders across Commercialization, R&D, Manufacturing, Enabling Functions, and the AI Accelerator Hub to align shared patterns with business and technology needs.
Communicate technical decisions and trade-offs clearly to both technical teams and stakeholders.
Help pod teams prepare successful POCs for Scale phase by aligning them with enterprise architecture, security, and operational standards.
Embed responsible AI practices, including basic safety, evaluation, and guardrail considerations, into shared components and reference architectures.
Qualifications & Experience:
Bachelor's degree in Engineering, Science, Business, or a related field.
3+ years of experience in software engineering, data science, AI, or related technology roles with increasing responsibility.
Proven track record designing and delivering GenAI and traditional software applications, as well as reusable platforms, libraries, or shared components.
Deep expertise in Python.
Strong experience with MCP, context engineering, multi-modal GenAI inputs, and vector databases.
Deep experience with AWS; familiarity with Azure and/or GCP is a plus.
Practical experience with Azure OpenAI and AWS Bedrock
Effective use of coding agents (e.g., Claude Code, Codex, Gemini CLI).
Comfort with GitHub and DevOps practices
Experience with Databricks, Terraform/CloudFormation, MLOps, or app observability is a plus.
Knowledge of and experience in agile ways of working
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Additional Information
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: careers.bms.com/working-with-us .
Position Summary :
As a Senior AI Engineer within Bristol Myers Squibb's AI Venture Studio Hub team, you will be a senior individual contributor focused on building the shared patterns, templates, components, and best practices that power Accelerator projects across Commercialization, R&D, Manufacturing, and Enabling Functions. You will spend much of your time hands-on in technical architecture, system and solution design, and building cloud-native GenAI platforms and reference implementations. You will create reusable GenAI building blocks and delivery patterns that enable AI Accelerator projects to move faster and smarter, and potentially step in to support or augment AI Accelerator pod teams when they encounter complex technical challenges.
Partnering closely with business, product, and technology stakeholders, you will promote responsible AI practices and help prepare successful proofs of concept for scalable, enterprise-wide adoption. As a senior engineer on the team, you will help set technical direction through influence, high standards, and mentorship.