AI ML Engineer — IT Infrastructure & Operations

Job Title

AI ML Engineer — IT Infrastructure & Operations

Role Summary

Work with the EDA/HPC Infrastructure team to design and deploy AI-powered solutions that improve engineering productivity, automate operations, accelerate troubleshooting, and optimize compute infrastructure for semiconductor design workloads.

Primary focus: building production-grade Generative AI applications, Agentic AI workflows, RAG systems, and integrations with on-prem and cloud infrastructure (Linux, storage, networking, schedulers, AWS).

Experience Level

Mid-level — 4–6 years of professional software development experience, especially with Python and infrastructure/AI systems.

Responsibilities

Deliver AI and automation solutions that integrate with infrastructure and engineering workflows. Key duties include:

• Design, develop, and deploy enterprise-grade AI applications and backend services using Python.
• Build AI assistants, copilots, RAG systems, and agentic AI agents for operations and engineering use cases.
• Implement Agentic AI workflows for reasoning, planning, tool execution, remediation, and orchestration.
• Implement RAG solutions using vector databases and optimize semantic search.
• Develop automation workflows (e.g., n8n) and integrate with enterprise APIs and systems.
• Integrate AI solutions with Linux servers, storage, networking, schedulers, and monitoring tools.
• Work with cloud-native AI services and infrastructure on AWS and hybrid environments.
• Implement monitoring, logging, testing, and governance controls for production AI systems.
• Participate in architecture reviews, design discussions, and technology evaluations.

Requirements

Must-have technical skills and experience:

• 4–6 years professional experience in software development with Python and API development.
• Proven experience designing and deploying Agentic AI / multi-agent systems and AI chatbots in production.
• Experience building RAG systems, vector databases, and semantic search optimizations.
• Experience with frameworks and tools such as LangChain, LangGraph, n8n, and AWS AgentCore.
• Strong Linux administration and scripting skills.
• Solid understanding of compute infrastructure, enterprise storage, networking fundamentals, and distributed systems.
• Experience with cloud platforms and cloud-native AI services (AWS; familiarity with Azure ML, SageMaker is a plus).
• Familiarity with Git workflows, CI/CD, MLOps practices, and model training pipelines.
• Ability to develop backend services, APIs, and integrations; experience with monitoring and governance for production AI.
• Willingness to travel approximately 10%.

Education Requirements

Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field — or equivalent practical experience.

About the Company

Company: Analog Devices

Headquarters: Norwood, Massachusetts, USA

Analog Devices is a leading global semiconductor company that bridges the physical and digital worlds, enabling breakthroughs at the Intelligent Edge. With a focus on innovation, ADI develops solutions that drive advancements in digitized factories, mobility, and digital healthcare. The company employs around 24,000 people globally and reported revenues exceeding $9 billion in FY24, creating technologies that transform lives across various sectors.