Principal Research AI Innovation Lead

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate with scientists and research leaders to pinpoint significant opportunities where AI can enhance research speed, quality, consistency, traceability, and decision-making.

• Contribute to the development of multi-year GenAI strategies, lead workstreams, and create reusable components—agentic frameworks, evaluation harnesses, retrieval and grounding components, tool servers, prompt and policy libraries, and provenance infrastructure—for research programs.

• Design and personally implement the agentic system-of-systems that carries out complex, long-term scientific workflows across research, including target evidence assembly, indication rationale construction, biomarker interpretation, translational synthesis, literature and evidence triangulation, and decision support, with a focus on inter-agent coordination, state and memory management, verification, recovery from intermediate failures, and lifecycle governance of agents in production.

• Set the scientifically rigorous evaluation, benchmarking, and reliability standards that essential research AI systems must meet, encompassing curated benchmark datasets, expert-reviewed reference standards, rubric-based assessments, hallucination and grounding metrics, uncertainty calibration, longitudinal monitoring, regression gating in production, and the governance surrounding those standards.

• Create mechanisms to integrate expert feedback, scientific rationale, provenance, and research context into AI workflows to ensure systems and institutional knowledge evolve over time.

• Work alongside engineering, data, IT, security, legal, vendor, and platform teams to guarantee prototypes are developed with suitable governance, integration pathways, and scalability in consideration.

• Clearly communicate AI opportunities, risks, limitations, evidence quality, and results to scientific, technical, and executive audiences.

• Keep abreast of emerging AI methods, tools, vendors, and industry practices, and evaluate where they can deliver tangible value for Research.

⛳️ Requirements

• Bachelor's Degree

• 8+ years of academic or industry experience

• Or a Master's Degree

• 6+ years of academic or industry experience

• Or a PhD

• 4+ years of academic or industry experience

• An advanced degree, such as MS, PhD, PharmD, or equivalent experience in a scientific, computational, or AI-related field.

• Direct experience in one or more research domains such as target identification and evaluation, indication expansion, drug repurposing, biomarker discovery, translational research, clinical evidence review, or portfolio decision support.

• Capability to interpret scientific evidence, assess analytical quality, and determine whether AI-generated scientific outputs are grounded, appropriately caveated, and defensible.

• Significant hands-on architectural expertise in modern AI and large language model methods, including agentic workflows, multi-agent orchestration, long-horizon task execution, GraphRAG, Model Context Protocol (MCP) authentication patterns, and deep research workflows with reasoning models, possessing the depth to establish reference architectures and architectural standards rather than simply integrating vendor APIs.

• Experience in constructing AI systems that reason across diverse scientific evidence, such as genetic associations, clinical outcomes, literature, omics data, assay data, real-world data, or other biomedical data sources.

• Experience in designing AI evaluation frameworks, benchmark datasets, human-reviewed reference standards, rubric-based assessments, or scientific quality metrics.

• Proven experience in developing or adapting deep learning models for biological, biomedical, or translational research applications, which includes fine-tuning biology-focused large language models, multimodal generative models, protein or sequence foundation models, representation-learning models, or other domain-specific AI systems.

• Background in innovation-lab, accelerator, startup, skunkworks, or rapid-prototyping settings.

🏝️ 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.

• Phoenix, AZ, Puerto Rico, and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires subject to manager approval, 11 national holidays, and 3 optional holidays.

• Depending 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 Year's Day.

• All global employees, full-time and part-time, who are actively employed at and compensated directly by BMS at the conclusion of the calendar year are eligible to benefit from the Global Shutdown.