Staff AI Software Platform Engineer

Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay ahead of what's possible. Learn more at .

Staff AI Platform Engineer

We're building a new AI Platform team, and we're looking for a mid to senior engineer to help shape it. This team is the backbone that lets the rest of the company build with AI safely, reliably, and cost effectively. We own the MLOps and LLMOps tooling, and we are the bridge to the cloud model providers we depend on (AWS Bedrock, Google Vertex AI, and others). You'll work alongside senior engineers who set the architectural direction, and you'll be trusted to own significant pieces of the platform yourself-building reusable components, APIs, and integration patterns that accelerate AI adoption across the enterprise.

What You'll Do

• Build and operate the platform and tooling our teams use to develop, deploy, and monitor AI powered applications.
• Create platform enablers-reusable components, APIs, and integration patterns-to make it faster and safer for teams to adopt AI.
• Own our integrations with cloud model providers (AWS Bedrock, Google Vertex AI), including usage, cost, and reliability.
• Serve as a key point of contact for internal users bringing us AI use cases-understand their needs, ask the right questions, and route them to the appropriate approach.
• Drive observability: ensure our systems are visible and debuggable through logging, metrics, and tracing.
• Contribute to and uphold AI engineering standards-security, compliance, cost, and governance-across our multi cloud environment.
• Grow into deeper MLOps/LLMOps ownership over time, and help level up the team's practices as it matures.

Must Have Skills

• Solid software engineering fundamentals with strong, working Python; clean, maintainable code; Git; and task automation.
• Hands on experience with at least one major cloud provider (AWS preferred, but strong GCP/Azure experience welcome).
• Working knowledge of cloud fundamentals: IAM/permissions, networking basics, and cost awareness (GPU instances and model API calls add up fast).
• Docker and comfort working with containerized applications.
• A strong operations and reliability mindset-monitoring, reproducibility, logging, metrics, and tracing.
• Experience building or operating platforms, internal tooling, or services that other engineers depend on.
• Strong communication and a service mindset; approachable and ready to ask good questions.
• Demonstrated ability to learn fast; curiosity beats a fixed checklist of tools.

Foundational Knowledge

• LLM Landscape: how to call a hosted model via a gateway like Bedrock or Vertex AI, and the basics of tokens, cost, latency, and context limits.
• Retrieval Augmented Generation (RAG): why and how it grounds a model in proprietary data.
• Fine tuning: understanding that it's a training process requiring GPU compute (e.g., AWS EC2 GPU instances) and is heavier than prompting or RAG.
• Agentic AI: reasoning, planning, autonomous workflows, and orchestration frameworks (e.g., LangChain).

Nice to Have

• Exposure to CI/CD (GitHub Actions, GitLab CI, or similar).
• Exposure to Infrastructure as Code (Terraform, Pulumi, CloudFormation).
• Kubernetes, or a strong desire to learn it.
• Familiarity with the broader model provider ecosystem (OpenAI, Anthropic, Hugging Face, etc.).
• Hands on exposure to ML/LLM tooling or agentic systems.
• A background in distributed systems, scalability, or performance optimization for demanding workloads.

Preferred Education and Experience

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field (or equivalent practical experience).
• 4-6 years of platform engineering experience, ideally including cloud native infrastructure, backend services, or internal developer platforms.
• Experience delivering and operating production systems in cloud environments, with an eye to security and reliability.
• Exposure to the AI/ML or MLOps/LLMOps space is a strong plus; we're happy to teach depth to a strong platform engineer who wants to grow into it.

Why You'll Love Working at ADI

At Analog Devices, you'll be part of a collaborative and innovative team that shapes the future of technology. We offer a supportive environment focused on professional growth, competitive compensation and benefits, work life balance, and the opportunity to work on cutting edge projects that make a real impact. Continuous learning opportunities and mentorship from industry experts are available. Join us and help create technologies that bridge the physical and digital worlds, making a tangible difference in how people live, work, and connect.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.