Associate Director Research Engineering

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.

Associate Director Research Engineering

Location: Remote, but preference given to candidates within proximity to the Cambridge, Lawrenceville, San Diego, Brisbane, or Seattle Sites (strong preference for Cambridge MA)

Job Description:

The Associate Director is a service-oriented, forward-thinking team leader who is responsible for overseeing the collaborative design and development of scalable, innovative, cloud-based solutions, specifically within the Informatics and Predictive Sciences (IPS) department at Bristol Myers Squibb (BMS). This pivotal role requires a combination of technical expertise, strategic vision, and collaborative leadership to support LLM-based solutions that drive scientific advancements in drug discovery and development. Experience with LLM technologies will be crucial for developing innovative solutions and driving experimentation in scientific research and drug development. The Associate Director oversees work within the Research Engineering team and works closely with subject matter experts, product managers, and IT teams to ensure that architectural design, resourcing, product development and delivery align with business objectives, scientific needs, and technical best practices.

Responsibilities:

• Lead the hiring, oversight and mentoring of Research Engineering team members
• Drive key architectural decision-making via workshops and brainstorming sessions to solve for end use requirements and use cases
• Develop strategic architectural roadmaps and guidelines for engineers and developers to adopt
• Own the early robust build phase of successful prototypes and lead the transition to iterative development and maintenance
• Navigate and collaborate with multiple IT organizations to gain alignment and clear a path for engineers and developers to proceed with solution build
• Explore and pilot new LLM technologies to assess their potential integration into existing architecture.
• Provide thought leadership on emerging LLM and AI models and capabilities and drive experimentation in service to BMS use cases 
• Perform risk assessments on new or existing cloud architectures to identify cost, scalability, or any other infrastructure management concerns.
• Propose opportunities for enhanced operational support of new or existing infrastructure through cloud-native monitoring and testing suites.
• Engage directly with development teams to provide guidance on appropriate selection of programming languages, LLM evaluation frameworks, testing methodologies, and system scalability strategies.
• Map use cases to leverage existing capabilities and define solutions for new capabilities.
• Pick appropriate technologies for new solutions and ensure integration with enterprise infrastructure.
• Merge technical infrastructure where needed, defining consistent back end and front-end technologies.

Skills:

• Experience building and maintaining cloud-native applications using core AWS services such as IAM, S3, Athena, Lambda, Fargate, Bedrock, OpenSearch, etc.
• Advanced proficiency with Python, SQL, R, database design, and at least one front end development framework (React, Angular, Streamlit, or similar)
• Previous exposure to large-scale scientific systems design and integration patterns, including mapping use cases to best practice architectural and integration patterns
• Ability to deliver performance evaluations, benchmarking, and troubleshooting of AI or LLM-based applications
• Familiarity with containerization (Docker/ECS), Agile methodologies, and cloud-native development patterns.
• Experience building or enhancing a laboratory informati