Associate Director, Senior AI Engineer

Role Summary

As a Senior AI Engineer within Bristol Myers Squibb's AI Accelerator program, 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 work 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 Pod Leads to move faster, and 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.

Responsibilities

• AI Accelerator Patterns, Templates & Components: Design, build, and maintain shared GenAI architectures, templates, and reusable components used across AI Accelerator pods.
• Define and uphold 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: Serve as a senior technical leader on the Foundations & Frameworks team, driving execution and raising the bar through strong engineering practices.
• Mentor engineers through pairing, code reviews, design reviews, and hands-on guidance, helping develop skills and technical judgment.
• Support onboarding and knowledge transfer by contributing to internal documentation, playbooks, templates, and reusable examples.
• Help establish lightweight, effective ways of working aligned with agile delivery, rapid experimentation, and reuse-first thinking.
• Cross-Functional Collaboration, Scale & Responsible AI: 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, trade-offs, and platform roadmaps clearly to both technical teams and senior leadership.
• Help pod teams prepare successful POCs for Scale phase by aligning 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

• 5+ years of experience in software engineering, data science, 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; some experience with TypeScript and modern frontend development (e.g., React).
• 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.
• Demonstrated experience mentoring engineers and providing technical leadership through influence (e.g. design reviews, standards, reusable patterns).
• Excellent written and verbal communication skills across technical and executive audiences.

Education

• Bachelor's degree in Engineering, Science, Business, or a related field.

Skills

• GenAI architectures, templates, and reusable components
• LLM-based applications, context engineering, MCP servers, agentic systems, and multi-modal inputs
• Python; TypeScript; React
• AWS; Azure; GCP; Azure OpenAI; AWS Bedrock
• Databricks, Terraform/CloudFormation, MLOps, and observability
• Vector databases
• Coding agents (Claude Code, Codex, Gemini CLI)
• GitHub and DevOps practices
• Agile development and rapid experimentation
• Mentoring and technical leadership; strong written and verbal communication