Senior AI Engineer

Bristol Myers Squibb • Seattle, WA

1d • Hybrid

About The Position

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.

Requirements

• 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
• Knowledge of and experience in agile ways of working
• Experience supporting peers through code reviews, design reviews, and informal technical mentorship.
• Strong written and verbal communication skills across technical and non-technical stakeholders.

Nice To Haves

• Experience with Databricks, Terraform/CloudFormation, MLOps, or app observability is a plus.

Responsibilities

• 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.
• 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.
• 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.

Benefits

• Health Coverage: Medical, pharmacy, dental, and vision care.
• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Work-life benefits include: Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees) Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
• Based on eligibility, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
• All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees