Data & AI Platform Engineer II
Exelixis
Summary
The Engineer II - AI and Agentic is responsible for designing, building, and deploying production-grade agentic applications that automate multi-step IT and business workflows across Exelixis. This role delivers spec-driven, testable, and secure AI solutions, contributes to platform patterns and reusable components, while advancing the engineering standards.
Job description
Summary/Job Purpose
The Engineer II - AI and Agentic is responsible for designing, building, and deploying production-grade agentic applications that automate multi-step IT and business workflows across Exelixis. This role delivers spec-driven, testable, and secure AI solutions, contributes to platform patterns and reusable components, while advancing the engineering standards.
Essential Duties/Responsibilities
- Design and deliver end-to-end agentic applications and multi-agent workflows that automate IT and business processes.
- Convert prototypes into hardened, production-ready services with clear specifications, modular design, robust error handling, and comprehensive test coverage.
- Integrate LLMs, prompts, tools, APIs, and enterprise data sources (e.g., Bedrock, Databricks Mosaic AI, MCP servers) into reliable use cases.
- Implement CI/CD pipelines, automated evaluation harnesses, observability, and artifact versioning for AI/agent workloads.
- Author architecture notes, runbooks, SOPs, and technical documentation to support adoption, operability, and maintainability.
- Lead prompt/spec reviews, code reviews, threat modeling exercises, and release-readiness gates.
- Apply and evangelize secure-by-design and responsible AI principles, including data governance, privacy, and safe prompting aligned to organizational policy
- Contribute reusable components, patterns, and internal libraries to the platform
- Partner with product managers, security, and platform teams to translate business needs into scalable technical solutions
- Performs other duties as assigned
- Complies with all policies and standards
Supervisory Responsibilities
No supervisory responsibilities
Education/Experience/Knowledge/Skills & Abilities
Education
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field and 5 years of related experience; or
- Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field and 3 year or related experience; or
- Equivalent combination of education and experience.
Experience
- 2 - 4 years of relevant experience in AI application, data science, automation, or related technical work, including hands-on experience building or contributing to LLM-enabled applications, agentic workflows, API integrations.
- Strong hands-on experience building AI-enabled applications and agentic workflows on top of enterprise data platforms.
- Deep understanding of modern data and analytics ecosystems, including data engineering, metadata, governance, and platform integration patterns.
- Ability to translate business and analytical use cases into scalable, production-ready AI and data solutions.
- Experience working across AI, data, platform, and security teams to establish reusable patterns, standards, and best practices.
Knowledge, Skills and Abilities
Required
- Intermediate to Advanced proficiency in Python and/or JavaScript/TypeScript, including modular design, testing, and packaging.
- Intermediate proficiency with agent frameworks and agentic patterns: tool use, planning/execution loops, guardrails, evaluation, and prompt/version management.
- Intermediate proficiency building and consuming REST APIs, and integrating enterprise systems with OAuth/JWT, secrets management, and secure data handling.
- Intermediate proficiency with CI/CD, automated testing (unit/integration), linting, and observability for AI applications.
- Intermediate understanding of security best practices, architecture design principles, and responsible AI/data governance.
- Intermediate communication skills, written and verbal, and demonstrated ability to collaborate with cross-functional stakeholders and mentor junior engineers.
- Intermediate experience with cloud AI platforms — preferably AWS Cloud, AWS Bedrock, and Databricks Mosaic AI — and vector stores or retrieval-augmented generation (RAG) patterns.
- Intermediate knowledge of AI-native engineering using Claude Code, Codex, GitHub Copilot, or equivalent coding agents.
Preferred
- Experience delivering evaluation frameworks, red-teaming, or LLM observability tooling.
Travel Requirements
No travel is required for this position.
Requirements
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field and 5 years of related experience; or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field and 3 year or related experience; or Equivalent combination of education and experience.
- 2 - 4 years of relevant experience in AI application, data science, automation, or related technical work, including hands-on experience building or contributing to LLM-enabled applications, agentic workflows, API integrations.
- Strong hands-on experience building AI-enabled applications and agentic workflows on top of enterprise data platforms.
- Deep understanding of modern data and analytics ecosystems, including data engineering, metadata, governance, and platform integration patterns.
- Ability to translate business and analytical use cases into scalable, production-ready AI and data solutions.
- Experience working across AI, data, platform, and security teams to establish reusable patterns, standards, and best practices.
- Intermediate to Advanced proficiency in Python and/or JavaScript/TypeScript, including modular design, testing, and packaging.
- Intermediate proficiency with agent frameworks and agentic patterns: tool use, planning/execution loops, guardrails, evaluation, and prompt/version management.
- Intermediate proficiency building and consuming REST APIs, and integrating enterprise systems with OAuth/JWT, secrets management, and secure data handling.
- Intermediate proficiency with CI/CD, automated testing (unit/integration), linting, and observability for AI applications.
- Intermediate understanding of security best practices, architecture design principles, and responsible AI/data governance.
- Intermediate communication skills, written and verbal, and demonstrated ability to collaborate with cross-functional stakeholders and mentor junior engineers.
- Intermediate experience with cloud AI platforms — preferably AWS Cloud, AWS Bedrock, and Databricks Mosaic AI — and vector stores or retrieval-augmented generation (RAG) patterns.
- Intermediate knowledge of AI-native engineering using Claude Code, Codex, GitHub Copilot, or equivalent coding agents.
- Experience delivering evaluation frameworks, red-teaming, or LLM observability tooling.
Benefits
- 401(k) Matching
- Medical, Dental & Vision
- Life & Disability Insurance
- Flexible Spending Accounts
- Discretionary Annual Bonus
- Company Stock Purchase
- Long-Term Incentives
- 15 Vacation Days
- 17 Paid Holidays
- Up to 10 Sick Days
Company overview
Exelixis, Inc. is an oncology-focused biotechnology company headquartered in Alameda, California, that specializes in the discovery, development, and commercialization of innovative cancer treatments. Founded in 1994, the company has evolved into a multi-platform cancer organization with a proven track record in the challenging biotech sector. Exelixis is best known for its flagship molecule cabozantinib, an inhibitor of multiple tyrosine kinases including MET, AXL, VEGF receptors, and RET, which has led to several approved drugs for difficult-to-treat cancers. The company's portfolio includes four approved drugs, with two derived from cabozantinib, and it maintains a robust pipeline of next-generation cancer treatments. With approximately 1,500 employees across five continents, Exelixis operates as a publicly traded company (NASDAQ: EXEL) and has established strategic alliances with major pharmaceutical and biotechnology partners. The company's mission centers on transforming science into new treatments that give cancer patients and their families hope for the future, with every employee united in this ambitious cause.