AI ML Engineer (IT Infrastructure & Operations)
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What you'll do
- Design, develop, and deploy enterprise-grade AI applications using Python and modern Generative AI frameworks.
- Build and maintain AI-powered assistants, copilots, RAG systems, and autonomous AI agents for infrastructure and engineering operations use cases.
- Develop Agentic AI workflows capable of reasoning, planning, tool execution, remediation, and workflow orchestration.
- Implement Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories.
- Develop automation workflows using tools such as n8n and integrate them with enterprise systems and APIs.
- Collaborate with EDA/HPC infrastructure engineers to automate troubleshooting, incident management, root-cause analysis, and operational workflows.
- Integrate AI solutions with infrastructure platforms including Linux servers, storage systems, networking components, schedulers, and monitoring tools.
- Develop APIs, backend services, and integrations supporting AI applications.
- Work with cloud-native AI services and infrastructure on AWS.
- Implement monitoring, logging, testing, and governance controls for production AI systems.
- Leverage AI developer productivity tools such as Claude Code, GitHub Copilot, and similar coding assistants to accelerate solution delivery.
- Participate in architecture reviews, design discussions, and technology evaluations.
What they're looking for
- Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
- 4–6 years of professional software development experience with Python and API development
- Hands-on experience designing and building Agentic AI applications in production environments and enterprise grade solutions.
- Proven experience developing AI Chatbots and Retrieval-Augmented Generation (RAG) systems
- Experience with vector databases and semantic search optimizations.
- Experience with AI Agents and Multi-Agent / Agentic AI systems
- Experience with frameworks and libraries including LangChain, LangGraph, n8n, AWS AgentCore
- Strong Linux administration and scripting knowledge.
- Sound understanding of Compute infrastructure, Enterprise storage technologies, Networking fundamentals, Distributed systems
- Familiarity with Git-based development workflows and CI/CD processes.
- Experience training ML model with MLOps methodology and working in cloud platforms such as Azure ML Workspace, AWS Sagemaker
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
About Analog Devices
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 www.analog.com and on LinkedIn and X.
Position Summary
We are seeking a highly motivated AI Engineer with 4–6 years of experience in software development, Generative AI, and infrastructure automation. The ideal candidate will work closely with the EDA/HPC Infrastructure team, building AI-powered solutions that improve engineering productivity, automate operations, accelerate troubleshooting, and optimize compute infrastructure supporting semiconductor design workloads.
This role requires a unique combination of Python development expertise, Generative AI engineering, AI Agent development, and strong infrastructure knowledge across compute, storage, networking, Linux, cloud (AWS), and on-premises environments.
Key Responsibilities
- Design, develop, and deploy enterprise-grade AI applications using Python and modern Generative AI frameworks.
- Build and maintain AI-powered assistants, copilots, RAG systems, and autonomous AI agents for infrastructure and engineering operations use cases.
- Develop Agentic AI workflows capable of reasoning, planning, tool execution, remediation, and workflow orchestration.
- Implement Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge repositories.
- Develop automation workflows using tools such as n8n and integrate them with enterprise systems and APIs.
- Collaborate with EDA/HPC infrastructure engineers to automate troubleshooting, incident management, root-cause analysis, and operational workflows.
- Integrate AI solutions with infrastructure platforms including Linux servers, storage systems, networking components, schedulers, and monitoring tools.
- Develop APIs, backend services, and integrations supporting AI applications.
- Work with cloud-native AI services and infrastructure on AWS.
- Implement monitoring, logging, testing, and governance controls for production AI systems.
- Leverage AI developer productivity tools such as Claude Code, GitHub Copilot, and similar coding assistants to accelerate solution delivery.
- Participate in architecture reviews, design discussions, and technology evaluations.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
- 4–6 years of professional software development experience with Python and API development
- Hands-on experience designing and building Agentic AI applications in production environments and enterprise grade solutions.
- Proven experience developing:
- AI Chatbots
- Retrieval-Augmented Generation (RAG) systems
- Experience with vector databases and semantic search optimizations.
- AI Agents
- Multi-Agent / Agentic AI systems
- Experience with frameworks and libraries including LangChain, LangGraph, n8n, AWS AgentCore
- Strong Linux administration and scripting knowledge.
- Sound understanding of Compute infrastructure, Enterprise storage technologies, Networking fundamentals, Distributed systems
- Familiarity with Git-based development workflows and CI/CD processes.
- Experience training ML model with MLOps methodology and working in cloud platforms such as Azure ML Workspace, AWS Sagemaker
Soft Skills
- Strong troubleshooting, analytical, and problem-solving skills.
- Effective communication and teamwork skills.
- Ability to manage multiple priorities in a fast-paced environment.
- Customer-focused mindset.
- Experience with project management is a plus.
For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.
Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their 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.
Job Req Type: ExperiencedRequired Travel: Yes, 10% of the time
Shift Type: 1st Shift/Days
Company
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