Associate Director, Research AI Delivery Lead - Raleigh

Gilead Sciences•Raleigh, NC

1d•Onsite

About The Position

As part of our enterprise AI strategy to speed life-changing therapies to patients, we are seeking a Data/AI Delivery Lead to lead the technical development and delivery of AI/ML solutions across Research. In this role, you will bridge the business needs of Research organization with technical execution and manage data science solution teams composed of internal resources and key external partners. You will drive technical excellence in our tailored AI solutions through hands-on architecture decisions, code quality standards and advanced analytics methodologies, delivering measurable impact to finance users from concept to scaled release.

Requirements

Bachelor's Degree and Ten Years' Experience OR Masters' Degree and Eight Years' Experience OR PhD and Two Years' Experience

Nice To Haves

Demonstrated experience leading AI/ML or advanced analytics delivery in Agile environments
Hands‑on background as data engineer, solution architect, or data scientist
Experience leading multi‑disciplinary, distributed delivery teams
Strong understanding of AI/ML architectures and data platforms
Experience in Research, or scientific computing environments preferred
Excellent stakeholder communication and technical leadership skills

Responsibilities

Own end-to-end delivery including timeline and technical quality of Research AI use case solutions from ideation through production
Apply product-centric approach with clear ownership, roadmaps, and user adoption metrics
Oversee the development of scalable solutions using Databricks, AWS, and Gilead ‘s Data & AI enterprise platforms
Lead hybrid technical delivery teams, drawing on technical experts within and beyond the team
Manage sprint planning, backlog prioritization and release schedules, extending into continuous improvement as both needs and the solution landscape evolves
Facilitate technical problem-solving across research domains
Ensure integration with existing data infrastructure and reusable components for common research patterns in key use cases (Research Knowledge Malmanagement Agents, Design- Build- Test- Learn cycle etc.)
Shape technical standards for research data models, storage and automation workflows
Maintain technical documentation and runbooks for research data pipelines and agents; Serve as escalation point for technical risks and delivery blockers
Track delivery metrics: cost reduction targets, process automation rates, weekly usage adoption
Manage vendor relationships and outsourced delivery with co-source providers
Monitor product performance & drive continuous improvement towards quantifiable targets; Track delivery, performance, and adoption metrics
Ensure compliance with data governance, security, and Research regulatory expectations
Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams.
Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current performance and future potential. They ensure employees are receiving the feedback and insight needed to grow, develop and realize their purpose.
Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem.