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Exelixis

Biopharmaceutical oncology company developing cancer therapies

Director – AI and Agentic Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeAlameda, CA, USA

About the Job

Requirements

  • Bachelor’s degree in a related discipline and 13 years of related experience, or a master’s degree in a related discipline and 11 years of related experience, or an equivalent combination of education and experience.
  • At least 5 years of experience in AI engineering or cloud platform engineering.
  • Leadership experience overseeing cross-functional teams.
  • Experience in full-lifecycle system development, including design, implementation, validation, and support of cloud-based solutions and platforms.
  • Advanced understanding of AI engineering, generative AI, agentic AI patterns, AI platform architecture, software engineering, cloud-native design, enterprise integration, and production operations.
  • Ability to define platform strategy, product roadmaps, business cases, success metrics, delivery plans, and adoption approaches for enterprise AI capabilities.
  • Hands-on technical credibility with modern AI solution patterns, including large language models, prompt and context engineering, tool use, multi-step workflows, agent orchestration, retrieval-augmented generation, vector search, evaluation, monitoring, and guardrails.
  • Experience with cloud AI and data platforms such as AWS, Amazon Bedrock, Databricks Mosaic AI, or equivalent technologies; familiarity with APIs, event-driven architectures, data pipelines, identity, secrets management, and enterprise security patterns.
  • Demonstrated ability to lead AI-native engineering practices using coding agents, AI-assisted development tools, specification-driven development, automated testing, continuous integration and continuous delivery, DevSecOps, observability, and continuous improvement.
  • Strong understanding of responsible AI, data governance, privacy, cybersecurity, model risk, auditability, human-in-the-loop controls, regulatory expectations, and enterprise policy compliance.
  • Ability to recruit, mentor, coach, and develop diverse technical teams while setting standards for quality, accountability, innovation, and delivery.
  • Ability to communicate complex AI concepts as business implications, risks, tradeoffs, and decisions, and to facilitate stakeholder alignment and influence outcomes.
  • Ability to work in ambiguous and fast-changing environments, make informed tradeoffs, resolve conflicts, and align cross-functional teams around outcomes.
  • Planning, portfolio management, vendor management, financial management, and execution skills, including managing multiple initiatives across a matrixed organization.

Responsibilities

  • Define and execute the AI engineering strategy, roadmap, and operating model for enterprise AI platforms, reusable services, and AI-enabled business solutions.
  • Lead the design and delivery of scalable AI platform capabilities, including model access patterns, agent orchestration, retrieval-augmented generation, evaluation frameworks, prompt and artifact management, observability, governance controls, and reusable integration patterns.
  • Oversee end-to-end development of production-grade generative AI, agentic AI, and automation solutions that improve productivity, decision support, operational efficiency, and business outcomes across functions.
  • Apply product management practices, including opportunity assessment, stakeholder discovery, prioritization, roadmap planning, user experience definition, value measurement, adoption planning, and lifecycle management.
  • Partner with business leaders, product managers, architects, data teams, cybersecurity, privacy, legal, compliance, and enterprise application teams to translate strategic business needs into secure, governed, and scalable AI solutions.
  • Establish AI-native engineering standards and practices, including specification-driven development, agent-assisted software delivery, automated testing, code quality, reusable patterns, DevSecOps, continuous integration and continuous delivery, release management, and operational support models.
  • Ensure AI solutions are designed for reliability, security, scalability, auditability, explainability, human oversight, measurable autonomy, and responsible AI use consistent with company policies and regulatory expectations.
  • Manage platform and technology decisions across AI providers, cloud services, data platforms, development tools, and open-source components; assess build-versus-buy options and total cost of ownership.
  • Create and monitor success metrics for AI platforms and solutions, including adoption, productivity impact, quality, latency, cost, risk reduction, reuse, user satisfaction, and business value realization.
  • Lead architecture reviews, prompt and solution reviews, security reviews, model and agent evaluations, release-readiness assessments, and post-production performance monitoring.
  • Develop talent, delivery practices, technical documentation, playbooks, reference architectures, and enablement materials to help teams adopt AI-native engineering safely and effectively.
  • Perform other duties as assigned.
  • Comply with all policies and standards.
  • Recruit staff to meet the unit’s immediate objectives and develop staff to meet longer-term objectives.
  • Appraise the performance of subordinates and recommend changes regarding job, pay, and employment status.
  • Assist with operating budgets and capital budgets if required, and control expenses to adhere to approved budgets.
  • Keep informed of company policies and procedures and current with technical and regulatory developments to ensure compliance.
  • Develop policies and procedures or recommend revisions to facilitate the accomplishment of the unit’s objectives.
  • Cooperate with management and staff of other organizational units to accomplish overall organizational objectives.
  • Provide a safe workplace and ensure employees are aware of and adhere to safety policies and procedures.
  • Travel up to 10% of the time.

Desired Qualifications

  • Knowledge of life sciences, biotechnology, clinical, regulatory, GxP, SOX, 21 CFR Part 11, or validated system environments.

About the Company

Exelixis

Biopharmaceutical oncology company developing cancer therapies

Exelixis develops and commercializes medicines for cancer. Its products aim to treat advanced cancers, including renal cell carcinoma, by targeting multiple biological pathways and supporting combination regimens to achieve effective, tolerable, and durable responses. The company generates revenue from sales of approved therapies and strategic partnerships, backed by extensive research, clinical trials, and regulatory approvals to bring new drugs to market. Compared with peers, Exelixis focuses on a pipeline that combines multi-pathway targeting with combination therapies to improve patient outcomes. Its overall goal is to advance cancer treatment and offer patients better chances of remission through its ongoing drug development programs.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
1994

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