Assoc Director, IT Systems Engineering (United States - North Carolina - Raleigh)

This job is with Gilead Sciences Inc., an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.

 

Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact.

 

We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.

Job Description

 

Architecture & Platform Strategy

• Define and evolve the target-state architecture for the self-serve data, AI, and agentic AI platform, aligned to enterprise strategy, data mesh principles, and regulatory requirements

• Establish enterprise standards and reference architectures for data products, semantic layer services, AI/LLM gateways, agent orchestration, and API- and MCP-based data access

• Architect the platform layers that let AI systems and agents find, trust, ask, and act on enterprise data - including data product interfaces, semantic context services, and governed write/action patterns

• Define tiered certification and governance patterns that scale data product trust from registered assets to autonomous-grade, AI-ready products

• Establish foundational patterns for retrieval, context enrichment, grounding, and tool exposure (RAG, semantic layer, MCP tool surfaces) to support agentic and real-time decisioning use cases

Engineering & Infrastructure

• Lead engineering of scalable, secure platform infrastructure on AWS (S3, Lake Formation, Glue, EKS, Bedrock, IAM, networking) and Databricks (Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, Mosaic AI)

• Engineer the agentic AI platform stack: agent runtimes, orchestration, agent identity and access management, action/write contracts, evaluation harnesses, and observability

• Implement platform engineering best practices: infrastructure-as-code (Terraform), CI/CD, automated testing, environment promotion, and GxP/Part 11-compliant change management

• Drive operational excellence across reliability, cost management (FinOps for data and AI workloads), observability, and incident response, grounded in SRE and Well-Architected practices

• Ensure security, data protection, and access governance patterns (fine-grained entitlements, row/column-level controls, audit lineage) meet regulated-industry requirements

Delivery Leadership & Product Management

• Contribute to the platform product roadmap: define outcomes, prioritize the backlog, and sequence capability delivery against enterprise AI adoption goals

• Lead delivery across a team of vendor partners, holding the team to clear standards for quality, velocity, and operability

• Drive build/buy/adopt decisions with rigor - vendor evaluation, kill criteria, and total-cost analysis - and integrate acquired capabilities into a coherent platform experience

• Define and track platform health and adoption metrics (DORA, reliability SLOs, self-serve adoption, time-to-data-product) and report progress to senior leadership

• Serve as a trusted advisor and technical leader: mentor engineers, run architecture reviews, and partner with business domains to identify and enable high-value data and AI use cases

• Communicate architecture and trade-offs crisply to audiences from engineers to Director/VP. stakeholders, simplifying complexity without losing rigor

Basic Qualifications

• 10+ years in platform engineering, data engineering, or enterprise data/AI platform architecture, including 3+ years leading engineering teams or major platform programs

• Deep hands-on expertise with AWS data and AI services, including S3, Lake Formation, Glue, EKS, Bedrock, Kinesis/MSK, IAM, and Terraform-based infrastructure automation

• Strong production experience with Databricks: Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, and workspace/governance administration at enterprise scale

• Demonstrated experience designing or building agentic AI or LLM-powered systems: agent orchestration, RAG pipelines, LLM gateways, tool/function calling, MCP or comparable protocols, and AI evaluation/observability

• Proven ability to build resilient, scalable pipelines for high-volume batch and streaming data, with proficiency in SQL and Python (or Scala/Java)

• Strong understanding of distributed systems, event-driven architecture, workflow orchestration, and API-first integration patterns

• Experience designing secure, governed, production-grade cloud architectures, including fine-grained access control, lineage, and auditability

• Track record of delivery leadership: roadmap ownership, backlog management, cross-functional coordination, and shipping platform capabilities that achieve measured adoption

• Excellent communication skills with the ability to simplify complexity and influence senior decision-makers

Preferred Qualifications

• Experience in biopharma, life sciences, or other heavily regulated domains, with working knowledge of GxP, 21 CFR Part 11, and computer system validation

• Background in data mesh or federated data architectures, data product operating models, and domain enablement at enterprise scale

• Experience with semantic layer technologies, knowledge graphs, metadata/catalog platforms, and data contract frameworks

• Familiarity with FinOps for data and AI workloads, including cost attribution, chargeback/showback, and LLM token economics

• Experience managing large vendor/partner ecosystems and running structured vendor evaluations with defined success and kill criteria

• Product management experience or certification; familiarity with DORA metrics, SPACE framework, and platform-as-a-product operating models

• AWS Professional (Solutions Architect or Data Analytics) and/or Databricks certifications

 

The salary range for this position is: $168,980.00 - $218,680.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*.

For additional benefits information, visit:

* Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.

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Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic <