Job description

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Location San Diego, CA hybrid. Not remote. Position Summary As a Staff AI DevOps Engineer, you will help shape how AI transforms software development and infrastructure services across the organization. As a key technical member of the DevOps team, you will design and build secure, scalable, enterprise-grade AI solutions; including infrastructure for federated AI agents, MCP servers, and AI-augmented development workflows across AWS and Azure. You will work hands-on with teams across Infrastructure & Cloud Services and software development to solve complex technical challenges, establish sound engineering patterns, and enhance the end-to-end AI lifecycle; from experimentation, development, evaluation, and deployment to observability, governance, and continuous improvement. Through this work, you will accelerate the responsible adoption of reliable, production-ready AI solutions and improve how software teams build, deliver, and operate AI-enabled applications at enterprise scale. Responsibilities Design and implement AI infrastructure to support federated agent development and distributed deployment across the organization to streamline common infrastructure and cloud service requests and support tasks. Manage and orchestrate AI agents to generate architecturally sound code, ensuring adherence to enterprise standards and best practices. Build and maintain MCP (Model Context Protocol) servers and related infrastructure for agent communication, coordination, and enterprise integration. Accelerate code review processes by leveraging AI agents for automated analysis, quality checks, and architectural validation. Integrate AI models and APIs, including LLMs and generative AI, into the bot solutions to provide natural language understanding and intelligent responses. Develop and manage infrastructure-as-code (IaC) using tools like Terraform or Ansible to provision and configure resources on AWS, Azure. Establish robust monitoring, governance, and security frameworks for AI agent operations in enterprise environments. Implement and manage secure authentication and authorization systems for MCP servers, including OAuth flows and API security. Collaborate closely with product owners and internal customers to gather requirements and deliver solutions that improve efficiency and user experience. Act as a forward deployed engineer, working with different functional teams across the Infrastructure & Cloud Services department to coach on AI infrastructure best practices and guide adoption. Provide technical leadership in transitioning traditional development practices to AI-augmented approaches Mentor and guide junior engineers, promoting best practices in software development, AI integration, DevOps, Cloud and Platform Engineering. Listed responsibilities are an essential, but not exhaustive list, of the usual duties associated with the position. Changes to individual responsibilities may occur due to business needs. Requirements Typically requires a minimum of 8 years of professional software development experience with a demonstrated ability to architect and build scalable systems with a bachelor s degree; or 6 years with a master s degree; or equivalent experience. Experience with AI/ML infrastructure, agent orchestration, or similar AI-powered development tools. Proficiency in Python, TypeScript/JavaScript, and experience with AI/ML frameworks and libraries. Strong understanding of enterprise software architecture patterns and distributed systems design. Experience with cloud platforms (AWS, Azure) and infrastructure-as-code tools. Experience with Docker, Kubernetes, and container orchestration in production environments. Strong understanding of information security principles, OAuth 2.0/OpenID Connect flows, API security, and secure system design. Strong communication and mentoring skills with the ability to collaborate across different teams. Basic understanding of enterprise services like Microsoft 365 and IAM (Identity and Access Management) and their APIs (e.g., Microsoft Graph API, Azure AD). Excellent problem-solving skills and the ability to work in an innovative, fast-paced incubator environment. Preferred Demonstrated experience in a product or solutions-oriented role, creating tools for internal customers. Relevant certifications from AWS, Azure, or professional certifications in AI/ML are highly desirable. Knowledge of AWS services such as Agent Core, Bedrock, and Lambda, or similar services on Azure including AI Foundry, Agent Loop, and Azure Functions is a significant plus. Knowledge of MCPs/APIs and integration patterns for common enterprise tools like ServiceNow, Jira, Confluence, GitHub, etc., is a plus. Experience with AI agent frameworks, LLM integration, or Model Context Protocol (MCP) implementations. Background in building federated systems or multi-agent AI platforms. Experience with AI governance, security, and compliance in enterprise environments. Familiarity with code generation tools, automated testing frameworks, and AI-powered development workflows. Knowledge of vector databases, embedding systems, and retrieval-augmented generation (RAG) architectures. Previous experience managing transitions from traditional to AI-augmented development practices. #LI-HYBRID The estimated base salary range for the Staff AI DevOps Engineer role based in the United States of America is: $141,600 - $212,400. Should the level or location of the role change during the hiring process, the applicable base pay range may be updated accordingly. The range reflects long‑term growth in the role; therefore, most candidates are hired between the minimum and middle of the range. Placement depends on experience, skills, location, and internal equity. Additionally, all employees are eligible for one of our variable cash programs (bonus or commission) and eligible roles may receive equity as part of the compensation package. We offer a wide range of benefits as innovative as our work, including access to genomics sequencing, family planning, health/dental/vision, retirement benefits, and paid time off. We are a company deeply rooted in belonging, promoting an inclusive environment where employees feel valued and empowered to contribute to our mission. Built on a strong foundation, Illumina has always prioritized openness, collaboration, and seeking alternative perspectives to propel innovation in genomics. We are proud to confirm a zero-net gap in pay, regardless of gender, ethnicity, or race. We also have several Employee Resource Groups (ERG) that deliver career development experiences, increase cultural awareness, and offer opportunities to engage in social responsibility. We are proud to be an equal opportunity employer committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status, and genetic information. Illumina conducts background checks on applicants for whom a conditional offer of employment has been made. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable local, state, and federal laws. Background check results may potentially result in the withdrawal of a conditional offer of employment. The background check process and any decisions made as a result shall be made in accordance with all applicable local, state, and federal laws. Illumina prohibits the use of generative artificial intelligence (AI) in the application and interview process. If you require accommodation to complete the application or interview process, please contact accommodations@illumina.com. To learn more, visit: dol.gov. The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants.

Requirements

Must-haves

What if the work you did every day could impact the lives of people you know? Or all of humanity?
San Diego, CA hybrid. Not remote.
Design and implement AI infrastructure to support federated agent development and distributed deployment across the organization to streamline common infrastructure and cloud service requests and support tasks.
Manage and orchestrate AI agents to generate architecturally sound code, ensuring adherence to enterprise standards and best practices.
Build and maintain MCP (Model Context Protocol) servers and related infrastructure for agent communication, coordination, and enterprise integration.
Accelerate code review processes by leveraging AI agents for automated analysis, quality checks, and architectural validation.
Integrate AI models and APIs, including LLMs and generative AI, into the bot solutions to provide natural language understanding and intelligent responses.
Develop and manage infrastructure-as-code (IaC) using tools like Terraform or Ansible to provision and configure resources on AWS, Azure.
Establish robust monitoring, governance, and security frameworks for AI agent operations in enterprise environments.
Implement and manage secure authentication and authorization systems for MCP servers, including OAuth flows and API security.
Collaborate closely with product owners and internal customers to gather requirements and deliver solutions that improve efficiency and user experience.
Act as a forward deployed engineer, working with different functional teams across the Infrastructure & Cloud Services department to coach on AI infrastructure best practices and guide adoption.
Provide technical leadership in transitioning traditional development practices to AI-augmented approaches
Mentor and guide junior engineers, promoting best practices in software development, AI integration, DevOps, Cloud and Platform Engineering.

Nice-to-haves

Demonstrated experience in a product or solutions-oriented role, creating tools for internal customers.
Relevant certifications from AWS, Azure, or professional certifications in AI/ML are highly desirable.
Knowledge of AWS services such as Agent Core, Bedrock, and Lambda, or similar services on Azure including AI Foundry, Agent Loop, and Azure Functions is a significant plus.
Knowledge of MCPs/APIs and integration patterns for common enterprise tools like ServiceNow, Jira, Confluence, GitHub, etc., is a plus.
Experience with AI agent frameworks, LLM integration, or Model Context Protocol (MCP) implementations.
Background in building federated systems or multi-agent AI platforms.
Experience with AI governance, security, and compliance in enterprise environments.
Familiarity with code generation tools, automated testing frameworks, and AI-powered development workflows.
Knowledge of vector databases, embedding systems, and retrieval-augmented generation (RAG) architectures.
Previous experience managing transitions from traditional to AI-augmented development practices.

Application prep

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Keywords to mirror

aiawsazureapimlpythontypescriptjavascriptdockerkubernetesjirallm

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off