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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff AI DevOps Engineer - **Company:** Illumina, Inc - **Location:** San Diego, CA, United States - **Experience:** Expert - **Salary:** $141,600.0 - $212,400.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Microsoft Windows, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, Architectural Patterns, Confluence, JIRA, User Authentication, Microsoft Azure, Cloud Computing, Code Generation, Code Review, Cyber Security, DevOps, Programming Tools, Distributed Systems, Github, Identity and Access Management, Python (Programming Language), Machine Learning, OAuth, Openid Connect, Azure Active Directory, Cloud Services, Ansible, Tensorflow, Software Engineering, TypeScript, AI Infrastructure, Enterprise Software Applications, Large Language Models, Multi-Agent Systems, Software Security, Generative AI, Agentic-AI, Build Management, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Enterprise Integration, Machine Learning Operations, Virtual Agents, Model Context Protocol, Terraform, Natural Language Understanding, Serverless Computing, Docker, Servicenow - **Published:** October 15, 2026 - **Apply:** https://illumina.wd1.myworkdayjobs.com/illumina-careers/job/US---California---San-Diego/Staff-AI-DevOps-Engineer_43575-JOB-1 ## About the Role * 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. ## Description 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.