AI Operating System (AIOS) Leader

About Lilly

About Technology@Lilly

Key Responsibilities

• AIOS Strategy & Roadmap Ownership: Set and own the strategy, architecture, and phased roadmap for the AI Operating System — from Phase 1 Foundation through Phase 2 ML Lifecycle to Phase 3 R&D AI at Scale — ensuring each layer of the stack (Data, Compute, Model, Application) advances against committed timelines.
• Team Leadership & Talent Development: Lead, mentor, and grow the ML Engineering and Data Engineering teams, including matrixed specialists embedded with science squads through the ML Engineering Chapter; build a culture of ownership, craftsmanship, and continuous learning.
• AIOS Platform Ownership: Own delivery and continuous improvement of core AIOS platforms — LillyCode (AI-assisted development), LillyPod (on-prem GPU compute), the LLM Gateway (governed frontier model access), Weights & Biases (ML lifecycle management), Weka Fabric (high-performance storage), and BioNova (Scientific Desktop) — ensuring each meets scale, security, and reliability requirements.
• Cross-Stack Partnership: Partner with Enterprise Stack leadership (Cortex, Landing Zone, CATS/Hangar) to ensure AIOS and the Enterprise Stack remain complementary, with models built in AIOS flowing into enterprise agentic workflows and business requirements flowing back.
• Compute & Infrastructure Stewardship: Govern shared, self-service access to compute and storage (GPU scheduling via Run:ai, high-performance storage via Weka Fabric) across all Lilly scientific teams, balancing guaranteed quotas, over-quota bursting, and fair prioritization.
• Science Enablement: Work directly with research and science squads (e.g., genomic AI and pharmacogenomics teams) to apply AIOS capabilities to high-value problems, translating scientific compute and data needs into platform requirements.
• Governance & Security: Ensure AIOS platforms complete cybersecurity review and AI Registry registration, with data-residency safeguards, usage tracking, and cost attribution across models and compute — including in regulated (e.g., GxP) environments.
• Executive Communication & Advocacy: Represent AIOS to senior leadership and cross-functional stakeholders, articulating impact (e.g., active users, tokens processed, digital worker equivalents, time-to-insight) and building the case for continued investment.
• AIOS Strategy & Roadmap Ownership:
• Set and own the strategy, architecture, and phased roadmap for the AI Operating System — from Phase 1 Foundation through Phase 2 ML Lifecycle to Phase 3 R&D AI at Scale — ensuring each layer of the stack (Data, Compute, Model, Application) advances against committed timelines.
• Team Leadership & Talent Development:
• Lead, mentor, and grow the ML Engineering and Data Engineering teams, including matrixed specialists embedded with science squads through the ML Engineering Chapter; build a culture of ownership, craftsmanship, and continuous learning.
• AIOS Platform Ownership:
• Own delivery and continuous improvement of core AIOS platforms — LillyCode (AI-assisted development), LillyPod (on-prem GPU compute), the LLM Gateway (governed frontier model access), Weights & Biases (ML lifecycle management), Weka Fabric (high-performance storage), and BioNova (Scientific Desktop) — ensuring each meets scale, security, and reliability requirements.
• Cross-Stack Partnership:
• Partner with Enterprise Stack leadership (Cortex, Landing Zone, CATS/Hangar) to ensure AIOS and the Enterprise Stack remain complementary, with models built in AIOS flowing into enterprise agentic workflows and business requirements flowing back.
• Compute & Infrastructure Stewardship:
• Govern shared, self-service access to compute and storage (GPU scheduling via Run:ai, high-performance storage via Weka Fabric) across all Lilly scientific teams, balancing guaranteed quotas, over-quota bursting, and fair prioritization.
• Science Enablement:
• Work directly with research and science squads (e.g., genomic AI and pharmacogenomics teams) to apply AIOS capabilities to high-value problems, translating scientific compute and data needs into platform requirements.
• Governance & Security:
• Ensure AIOS platforms complete cybersecurity review and AI Registry registration, with data-residency safeguards, usage tracking, and cost attribution across models and compute — including in regulated (e.g., GxP) environments.
• Executive Communication & Advocacy:
• Represent AIOS to senior leadership and cross-functional stakeholders, articulating impact (e.g., active users, tokens processed, digital worker equivalents, time-to-insight) and building the case for continued investment.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, with 12+ years of relevant experience
• Proven experience owning a multi-layer AI/ML platform (data, compute, model, and application layers) in a large, matrixed enterprise
• Demonstrated leadership of both ML Engineering and Data Engineering functions, including managing leads across multiple squads
• Deep knowledge of GPU compute infrastructure, distributed training, and high-performance storage (e.g., GPU scheduling, parallel file systems)
• Experience governing frontier model access (e.g., multi-provider LLM gateways) including usage tracking, cost attribution, and vendor-agnostic architecture
• Track record of delivering ML lifecycle tooling (experiment tracking, model registry, dataset versioning) at enterprise scale
• Experience operating in regulated environments (GxP, SOX, CSV/CSA) within life sciences or another regulated industry
• Strong executive presence with experience presenting technical strategy and roadmap to senior leadership
• Experience partnering with enterprise application or agent-platform teams to ensure complementary, non-duplicative investment across stacks
• Core Competencies
• Platform & Technical Strategy • Organizational Leadership • Cross-Functional Partnership • Compute & Infrastructure Governance • AI/ML Lifecycle Expertise • Executive Communication • Talent Development • Delivery at Scale
• Additional Information
• Up to 10% travel, including international.
• Lilly does not discriminate on the basis of age, race, colour, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
• #WeAreLilly
• Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form ( https://careers.lilly.com/us/en/workplace-accommodation ) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
• Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
• Platform & Technical Strategy
• Organizational Leadership
• Cross-Functional Partnership
• Compute & Infrastructure Governance
• AI/ML Lifecycle Expertise
• Executive Communication
• Talent Development
• Delivery at Scale