This role pays more than
81%
of similar roles. Most pay
$168,687–$262,238
— the shaded band above.
At the midpoint, this role pays about
$279k
versus about
$215k
for comparable roles.
Based on 240 similar postings.
Employer
About Gilead Sciences
Gilead Sciences, Inc. is a leading American biopharmaceutical company specializing in discovering, developing, and commercializing innovative medicines for unmet medical needs.
Gilead Sciences currently has
29 open roles
on FindRole.
Listed pay typically runs
$169,320–$219,120
across 28 roles with salary data.
The Senior Director, Applied AI Solutions leads the applied AI function within the AI Research Center as part of the Clinical Data Science organization. This leader is responsible for the technical and product path of AI use cases, moving them from discovery and experimentation to trusted, reusable production capabilities. The role involves defining engineering practices such as model lifecycle management, agent design patterns, and solution architecture while overseeing the development of systems like RAG, semantic search, and knowledge graphs. Key technologies include LLMs, MLOps/LLMOps, and various interoperability protocols. The position addresses complex clinical data challenges, including study design, biomarker workflows, and regulatory evidence generation. By providing technical expertise and solution engineering, this role transforms high-value pharmaceutical research problems into production-grade AI tools to improve how the organization designs, conducts, and analyzes clinical development programs.
Translate prioritized AI demand into a multi-year engineering and delivery plan based on technical feasibility and risk assessment.
Lead the design, build, evaluation, and technical validation of AI services from initial concept to first production release.
Establish reference solutions for RAG, semantic search, knowledge graphs, and agentic systems while ensuring enterprise scalability.
Define and uphold engineering practices including model lifecycle management, LLMOps, automated testing, and reproducible releases.
Establish evaluation frameworks including gold-standard datasets, monitoring, and risk-tiered governance to ensure responsible AI usage.
Build and lead a high-performing multidisciplinary team of machine learning and software engineers through technical coaching and design reviews.
Provide expert guidance on "build vs. buy" decisions and manage strategic relationships with external AI vendors.
Measure and report the impact of AI solutions on scientific, operational, and quality outcomes for clinical development workflows.
What we're looking for
Bachelor’s degree with 14+ years experience, Master’s with 13+ years, or PhD with 12+ years in a relevant quantitative field.
Recent hands-on experience developing and maintaining AI systems, including writing code, reviewing pull requests, and troubleshooting production issues.
Substantial experience leading applied AI, ML, or data engineering organizations while remaining technically hands-on in complex enterprises.
Proven track record of delivering AI products from initial problem framing through to validated release and value measurement.
Deep knowledge of modern AI systems including LLMs, RAG, agent orchestration, evaluation, guardrails, and human-in-the-loop patterns.
Strong software engineering judgment regarding APIs, distributed systems, cloud services, MLOps/LLMOps, and production reliability.
Experience implementing AI in environments with rigorous privacy, security, quality, compliance, or regulatory requirements.
Experience in pharmaceutical, biotechnology, or healthcare domains (preferred).
AI Agents
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