Platform Delivery Lead, Data & AI
Gilead Sciences
August 15, 2026
Remote friendly (Raleigh, NC)
United States
IT
Platform Delivery Lead, Data & AI
Key Responsibilities:
- Own end-to-end delivery (timeline and technical quality) for Data & AI platform products from ideation through production and operations.
- Use a product-centric approach with ownership, roadmaps, service-level objectives, and adoption metrics.
- Oversee scalable, reusable platform capabilities built on AWS and Databricks as self-service products for use case/tenant teams.
- Enable shared AI services: model access, RAG/retrieval, evaluation, guardrails, orchestration.
- Create reusable assets/accelerators (agent templates, MCP tools/servers, prompt & evaluation libraries, reference patterns).
- Lead hybrid engineering teams (platform + data/AI engineers), including internal and external experts.
- Manage sprint planning, backlog prioritization, and release schedules; drive continuous improvement.
- Facilitate technical problem-solving across data engineering, AI/ML, agentic enablement, governance, and platform reliability.
- Ensure integration with the broader data/AI ecosystem using reusable components and patterns (ingestion frameworks, feature/serving infrastructure, shared services).
- Shape technical standards (architecture, data models, pipeline patterns, automation workflows).
- Maintain technical documentation, architecture references, and operational runbooks.
- Track platform health metrics (reliability/availability, adoption, time-to-onboard, operational efficiency).
- Manage co-source/vendor relationships.
- Monitor performance and drive measurable improvements (cost, resilience, engineering excellence).
Basic Qualifications:
- Bachelor’s + 8 years; OR Master’s + 6 years; OR PhD + 2 years experience.
Preferred Qualifications:
- Data/computer science degree; 8+ years (BA/BS) or 6+ years (MA/MS/MBA).
- Agile/Scrum leadership experience.
- Hands-on experience as lead data/platform engineer or solution architect.
- Strong AWS data/AI and Databricks expertise (e.g., S3, EKS, Lake Formation, Bedrock; Unity Catalog, Lakeflow/Delta Live Tables, model serving, Databricks apps).
- Experience with shared multi-tenant platforms and self-service developer experiences.
- Experience with large (15+) dispersed development teams.
- Product-centric mindset; modern data/AI architectures (data lakehouse, MLOps/LLMOps, API/event-driven, agentic/AI service patterns).
- Familiarity with governance/security/compliance in regulated environments (preferred).
- Strong leadership and stakeholder management.
People Leader Accountabilities:
- Create inclusion; develop talent; empower teams.
Benefits (if applicable):
- Salary range: $146,200.00–$189,200.00; may include bonus, stock incentives, paid time off, and company-sponsored medical/dental/vision/life insurance.
Application Instructions:
- Apply via the Internal Career Opportunities portal in Workday.
Key Responsibilities:
- Own end-to-end delivery (timeline and technical quality) for Data & AI platform products from ideation through production and operations.
- Use a product-centric approach with ownership, roadmaps, service-level objectives, and adoption metrics.
- Oversee scalable, reusable platform capabilities built on AWS and Databricks as self-service products for use case/tenant teams.
- Enable shared AI services: model access, RAG/retrieval, evaluation, guardrails, orchestration.
- Create reusable assets/accelerators (agent templates, MCP tools/servers, prompt & evaluation libraries, reference patterns).
- Lead hybrid engineering teams (platform + data/AI engineers), including internal and external experts.
- Manage sprint planning, backlog prioritization, and release schedules; drive continuous improvement.
- Facilitate technical problem-solving across data engineering, AI/ML, agentic enablement, governance, and platform reliability.
- Ensure integration with the broader data/AI ecosystem using reusable components and patterns (ingestion frameworks, feature/serving infrastructure, shared services).
- Shape technical standards (architecture, data models, pipeline patterns, automation workflows).
- Maintain technical documentation, architecture references, and operational runbooks.
- Track platform health metrics (reliability/availability, adoption, time-to-onboard, operational efficiency).
- Manage co-source/vendor relationships.
- Monitor performance and drive measurable improvements (cost, resilience, engineering excellence).
Basic Qualifications:
- Bachelor’s + 8 years; OR Master’s + 6 years; OR PhD + 2 years experience.
Preferred Qualifications:
- Data/computer science degree; 8+ years (BA/BS) or 6+ years (MA/MS/MBA).
- Agile/Scrum leadership experience.
- Hands-on experience as lead data/platform engineer or solution architect.
- Strong AWS data/AI and Databricks expertise (e.g., S3, EKS, Lake Formation, Bedrock; Unity Catalog, Lakeflow/Delta Live Tables, model serving, Databricks apps).
- Experience with shared multi-tenant platforms and self-service developer experiences.
- Experience with large (15+) dispersed development teams.
- Product-centric mindset; modern data/AI architectures (data lakehouse, MLOps/LLMOps, API/event-driven, agentic/AI service patterns).
- Familiarity with governance/security/compliance in regulated environments (preferred).
- Strong leadership and stakeholder management.
People Leader Accountabilities:
- Create inclusion; develop talent; empower teams.
Benefits (if applicable):
- Salary range: $146,200.00–$189,200.00; may include bonus, stock incentives, paid time off, and company-sponsored medical/dental/vision/life insurance.
Application Instructions:
- Apply via the Internal Career Opportunities portal in Workday.