Senior Software Engineer, RAG and Agentic AI

Responsibilities

• Plan, build, and refine GPU-accelerated, scalable, and configurable Retrieval Augmented Generation (RAG) workflows optimized for accuracy and performance.
• Design and implement AI agents capable of reasoning, planning, multi-step execution, and collaboration across various tools and services.
• Execute high-quality Proof of Concepts (POCs) on emerging agent and RAG architectures and harden successful patterns into production-grade software.
• Build and deploy end-to-end RAG pipelines using microservices architecture, orchestrating deployments from local Docker environments to enterprise-scale Kubernetes clusters.
• Drive continuous pipeline improvement by evaluating system accuracy, characterizing performance metrics, and recommending strategic enhancements.
• Collaborate with cross-functional teams to develop new product features and provide guidance on domain-adaptation and RAG integration.
• Champion engineering excellence through rigorous code reviews, architecture design, and the automation of CI/CD and telemetry workflows.

Requirements

• 5 years of professional software engineering experience with deep expertise in Python and AI applications.
• Hands-on experience building and deploying LLM-powered AI applications, RAG, or Agentic AI workflows.
• Strong understanding of LLM design patterns, including tool calling, prompt engineering, structured outputs, and reasoning.
• Experience with agent frameworks or orchestration systems such as LangChain, LangGraph, or OpenAI Agents SDK.
• Working experience with microservices, Docker, Helm, and Kubernetes.
• Experience with the full software development lifecycle, including release packaging and CI/CD pipelines.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, Data Science, Artificial Intelligence, or a related field.

Preferred Qualifications

• Experience designing multi-agent systems and sophisticated workflow orchestration engines.
• Familiarity with evaluation frameworks, MLOps pipelines, and AI observability tooling.
• Background in deploying AI models on data center, cloud, or embedded systems.
• Strong Python programming skills and experience working with AI coding agents.

About the Company

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing, where our GPUs act as the brains of computers, robots, and self-driving cars.