Senior AI and ML Software Engineer

NVIDIA•Us, CA

About The Position

We are looking for a highly motivated AI/ML Software Engineer to join the Enterprise Agentic AI Platform team within IT. You will work closely with Business Analysts, and Engineering teams to design, develop, and deploy enterprise AI solutions that improve productivity and automate business workflows across Engineering, Operations, and Manufacturing.

Requirements

Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, or a related field (or equivalent experience).
5+ years of software engineering experience with strong proficiency in Python and backend application development.
Hands-on experience with AL/ML, Generative AI, LLMs, RAG, AI agents, REST APIs, and cloud-native application development.
Experience integrating enterprise applications and building scalable, production-ready software solutions.
Strong analytical, problem-solving, communication, and collaboration skills.
Self-driven individual with the ability to work independently in a fast-paced environment.

Nice To Haves

Experience with AI/ML models, Agentic AI frameworks, Model Context Protocol (MCP), LangChain, LangGraph, Autogen, or Microsoft Agent Framework.
Experience with Azure AI Services, Azure OpenAI, AI Search, vector databases, or enterprise AI platforms.
Knowledge of Engineering, PLM, Manufacturing, or Supply Chain business processes.
Experience building enterprise AI copilots, intelligent assistants, or workflow automation solutions.

Responsibilities

Design, develop, and deploy Agentic AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI orchestration frameworks.
Build scalable AI services and reusable components integrated with enterprise applications such as PLM, SAP, and other business systems.
Build and deploy AI/ML models and applications for Manufacturing of Boards and Chips.
Collaborate with business and IT teams to translate business requirements into AI-driven solutions.
Develop secure, scalable APIs and enterprise integrations to enable intelligent workflows and automation.
Improve AI solution quality, performance, and reliability through prompt engineering, evaluation, and continuous optimization.
Partner with cross-functional teams throughout the Software Development Lifecycle (SDLC), from solution design through deployment and production support.