Kite Data & Integration Lead - Sales & Digital
Gilead Sciences
June 24, 2026
Remote friendly (Raleigh, NC)
United States
Sales
The Kite Data & Integration Lead - Sales & Digital (Data/AI Product Owner) will drive AI/data product strategy for Commercial Reporting & Analytics. Act as the primary liaison between GDDI, IT, and partners to build production-grade analytics infrastructure on AWS and Databricks. Translate evolving Commercial needs into a prioritized product roadmap, define success metrics tied to measurable business outcomes, and influence near- and long-term data/AI platform evolution. Own product vision, roadmap, and stakeholder engagement for AI-enabled reporting, planning, and analytics use cases.
Key Responsibilities
- ML & Data Engineering: Manage model lifecycle (CI/CD, testing, deployment) and support serving for patient identification, alignment prediction, next-best-action, and competitive intelligence; design batch/streaming workflows; ensure production reliability with monitoring (performance, drift, bias, service health) and data quality.
- Agentic AI & Agent Systems Engineering: Decompose business workflows into agent-executable workstreams; define boundaries between agent execution and human judgment; design prompt/instruction architecture (skills, memories, context); optimize token economics and execution cost.
- Governance, Security & Compliance: Implement version control, approvals, documentation, and audit trails; ensure explainable/auditable, compliant outputs (HIPAA/PHI, GDPR, FDA promotional regulations, REMS); enforce secrets management, RBAC, network policies, and data protection.
Collaboration & Enablement
- Partner across Brand, Market Access, Patient Services, and Field; accelerate delivery with frameworks/templates.
- Set up testing/validation for ML models and agent-generated code (quality gates, type checks, linting, integration/contract tests).
- Create guides, playbooks, user instructions; coordinate releases; maintain runbooks/rollback/change tickets.
Basic Qualifications
- Bachelor’s degree + 8 years’ experience OR Master’s degree + 6 years’ experience.
Preferred Qualifications (selected)
- 3+ years data engineering (scale deployments); 2+ years building analytics/data science solutions.
- Python, SQL; TDD/CI/CD; GitHub Actions, Docker; Databricks (Spark), Airflow, Tableau.
- Hands-on AI coding tools (e.g., Claude Code/GitHub Copilot/Cursor) and LLM serving (e.g., Cortex AI); prompt engineering.
- Healthcare security/privacy (HIPAA, SOC 2, 21 CFR Part 11), systems thinking.
People Leader Accountabilities
- Create inclusion; develop talent; empower teams.
Compensation/Benefits
- Salary range: Raleigh $146,200-$189,200; Bay Area $169,320-$219,120. May be eligible for bonus, stock-based incentives, paid time off, and benefits.
Application Instructions
- Apply via the Internal Career Opportunities portal in Workday.
Key Responsibilities
- ML & Data Engineering: Manage model lifecycle (CI/CD, testing, deployment) and support serving for patient identification, alignment prediction, next-best-action, and competitive intelligence; design batch/streaming workflows; ensure production reliability with monitoring (performance, drift, bias, service health) and data quality.
- Agentic AI & Agent Systems Engineering: Decompose business workflows into agent-executable workstreams; define boundaries between agent execution and human judgment; design prompt/instruction architecture (skills, memories, context); optimize token economics and execution cost.
- Governance, Security & Compliance: Implement version control, approvals, documentation, and audit trails; ensure explainable/auditable, compliant outputs (HIPAA/PHI, GDPR, FDA promotional regulations, REMS); enforce secrets management, RBAC, network policies, and data protection.
Collaboration & Enablement
- Partner across Brand, Market Access, Patient Services, and Field; accelerate delivery with frameworks/templates.
- Set up testing/validation for ML models and agent-generated code (quality gates, type checks, linting, integration/contract tests).
- Create guides, playbooks, user instructions; coordinate releases; maintain runbooks/rollback/change tickets.
Basic Qualifications
- Bachelor’s degree + 8 years’ experience OR Master’s degree + 6 years’ experience.
Preferred Qualifications (selected)
- 3+ years data engineering (scale deployments); 2+ years building analytics/data science solutions.
- Python, SQL; TDD/CI/CD; GitHub Actions, Docker; Databricks (Spark), Airflow, Tableau.
- Hands-on AI coding tools (e.g., Claude Code/GitHub Copilot/Cursor) and LLM serving (e.g., Cortex AI); prompt engineering.
- Healthcare security/privacy (HIPAA, SOC 2, 21 CFR Part 11), systems thinking.
People Leader Accountabilities
- Create inclusion; develop talent; empower teams.
Compensation/Benefits
- Salary range: Raleigh $146,200-$189,200; Bay Area $169,320-$219,120. May be eligible for bonus, stock-based incentives, paid time off, and benefits.
Application Instructions
- Apply via the Internal Career Opportunities portal in Workday.