Associate Principal, AI Engineering

About this role

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

Summary

The Associate Principal, AI Engineer is a senior technical leader who partners with Principal Architects, business stakeholders, and engineering teams to translate enterprise strategy into scalable, AI-enabled technology solutions. This role blends deep hands-on technical depth across full-stack engineering, cloud platforms, and modern AI architectures with the leadership presence needed to influence cross-functional teams and shape long-range technology direction. The successful candidate will architect production-grade systems that integrate Generative AI, agentic workflows, and RAG-based retrieval into core enterprise applications, while mentoring engineering teams and establishing the patterns, guardrails, and platforms that allow AI to scale responsibly across the organization.

Key Responsibilities Architecture and Technical Strategy • Define reference architectures, design patterns, and platform standards for AI-enabled enterprise applications spanning web, mobile, and backend services. • Partner with the Principal Architect to develop multi-year technology roadmaps that align cloud, data, AI, and application strategy with business objectives. • Evaluate emerging technologies (foundation models, agentic frameworks, vector databases, MLOps tooling) and translate them into actionable adoption plans. • Lead architectural reviews, ensuring system designs meet requirements for scalability, security, performance, observability, and total cost of ownership.

AI and Generative AI Engineering • Architect Generative AI solutions including RAG systems, multi-agent workflows, conversational interfaces, and domain-specific fine-tuned models. • Design responsible AI frameworks covering prompt engineering standards, evaluation pipelines, model governance, and content safety controls. • Establish MLOps and LLMOps practices for model deployment, monitoring, drift detection, and continuous improvement. • Integrate LLM providers (OpenAI, Anthropic, Google) and orchestration frameworks (LangChain, LangGraph) into production systems with appropriate fallback and cost controls.

Cloud and Platform Engineering • Design cloud-native solutions on Google Cloud Platform, Azure, or AWS, leveraging managed AI services (Vertex AI, AlloyDB, Cloud Functions, equivalent services). • Architect CI/CD pipelines, infrastructure-as-code, and platform automation that accelerate engineering velocity without compromising reliability. • Define and enforce standards for containerization, microservices, API design, and event-driven architectures.

Leadership and Delivery • Provide technical leadership to engineering teams of 15 to 30 engineers, including UI developers, backend engineers, ML engineers, and platform specialists. • Mentor senior engineers and tech leads, growing the next generation of architects within the organization. • Partner with product, design, and business stakeholders to scope initiatives, manage trade-offs, and deliver measurable business outcomes. • Represent the architecture function in executive forums, vendor evaluations, and strategic planning sessions.

Required Qualifications • 15 or more years of progressive experience in software engineering, with at least 5 years in architecture or senior technical leadership roles. • Deep hands-on expertise across full-stack development, including Python and Java ecosystems (Spring Boot, Spring Cloud, microservices). • Proven experience architecting and deploying Generative AI solutions in production, including RAG systems, prompt engineering, and LLM integration. • Strong command of at least one major cloud platform (GCP, Azure, or AWS), with demonstrated experience designing scalable, multi-tenant systems. • Experience leading distributed engineering teams of 15 or more across multiple time zones. • Track record of delivering enterprise-grade systems that serve large user bases with measurable performance and revenue outcomes. • Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.

Preferred Qualifications • Experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI) and multi-agent system design. • Familiarity with Voice AI and conversational AI platforms, including ASR, TTS, and dialog management. • Background in commerce platforms (Bloomreach, Salesforce Commerce Cloud, Adobe Experience Cloud) or industrial and B2B e-commerce. • Exposure to data platforms (BigQuery, Snowflake, Databricks) and modern data architectures (lakehouse, streaming, vector stores). • Industry certifications such as TOGAF, GCP Professional Cloud Architect, Azure Solutions Architect Expert, or AWS Solutions Architect Professional. • Active engagement with the technology community through conference talks, publications, patents, or industry awards. • Senior membership in IEEE, ACM, or equivalent professional organization.

Technical Skill Profile • AI and Machine Learning:  Generative AI, LLMs (GPT-4, Claude, Gemini), LangChain, LangGraph, RAG architectures, vector search, prompt engineering, fine-tuning, MLOps, responsible AI, multi-agent systems, Voice AI, semantic search. • Programming and Frameworks:  Python, Java SE, Spring Boot, Spring MVC, Spring JPA, Spring REST, Spring Cloud, Hibernate, REST and GraphQL API

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