Senior Software Engineer, RAG and Agentic AI

What you’ll be doing:

• Plan, build and refine a GPU-accelerated, scalable, configurable Retrieval Augmented Generation (RAG) workflow and optimize it for accuracy, relevance, grounding and performance.

• Design and implement AI agents to enhance RAG pipeline which are capable of reasoning, planning, multi-step execution, and collaboration across tools and services

• Run fast, high-quality POCs on emerging agent and RAG architectures; harden successful patterns into generalized, reusable implementations and integrate them as part of production software.

• Build and deploy a disaggregated, end-to-end RAG pipeline using on-prem microservices architecture, orchestrating complex, multi-service deployments from local Docker environments to enterprise-scale Kubernetes clusters.

• Drive the continuous improvement of the pipelines by rigorously evaluating system accuracy, characterizing performance metrics across components, analyzing the data and recommending actionable strategic enhancements."

• Collaborate with various teams on new product features and the improvement of existing product. Provide guidance and support to NVIDIA internal teams and external partners on domain-adaptation, customization and integration of the RAG pipeline.

• Champion engineering excellence by leading rigorous code, architecture, and test plan reviews, authoring robust user documentation, and driving collaborative problem-solving and triage initiatives.

• Drive software excellence by designing with clean architectural patterns and automating the path to production through advanced CI/CD, testing, and telemetry workflows.

What we need to see:

• 5+ years of professional software engineering experience, with deep expertise in Python, and AI applications.

• Bachelor's degree or Master’s degree (or equivalent experience) in Computer Science, Electrical Engineering, Data Science, Artificial Intelligence or other related fields

• Hands-on experience building and deploying LLM-powered AI applications or RAG or Agentic AI workflows.

• Strong understanding of LLM design patterns, including tool calling, prompt engineering, structured outputs, reasoning.

• Experience with agent frameworks or orchestration systems such as LangGraph, LangChain, OpenAI Agents SDK, or similar.

• Have working experience with microservices, Docker, Helm, Kubernetes.

• Experience with end-to-end software lifecycle, release packaging, and CI/CD pipelines.

• Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic environment involving teams across the globe.

Ways to stand out from the crowd:

• 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, and embedded systems.

  • Strong python programming skills and experience of working with AI coding agents.