Senior Software Engineer, RAG and Agentic AI

Posted Yesterday
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Build and productionize GPU-accelerated Retrieval-Augmented Generation (RAG) and agentic AI pipelines. Design AI agents, run POCs, harden reusable components, deploy microservices to Kubernetes, improve accuracy and performance, collaborate cross-functionally, and drive CI/CD, testing, and observability for enterprise AI solutions.
Summary Generated by Built In

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

We are looking for a Senior Software Engineer to join our AI Blueprints team to build multimodal, scalable, production-grade reference RAG solutions. In this role you will build the next-generation RAG architecture using Agentic AI and NVIDIA Nemotron models and develop orchestration layers to dynamically interact with proprietary unstructured and structured data sources. If you are creative and passionate about real-world enterprise AI challenges, come join us.

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.

NVIDIA is committed to encouraging a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees. We do not discriminate in hiring or promotion based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected characteristic.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

Skills Required

  • 5 years of professional software engineering experience
  • Deep expertise in Python
  • Bachelor's or Master's degree (or equivalent experience) in Computer Science, EE, Data Science, AI or related field
  • Hands-on experience building and deploying LLM-powered AI applications, RAG, or Agentic AI workflows
  • Strong understanding of LLM design patterns (tool calling, prompt engineering, structured outputs, reasoning)
  • Experience with agent frameworks or orchestration systems such as LangGraph, LangChain, OpenAI Agents SDK, or similar
  • Experience with microservices, Docker, Helm, and Kubernetes
  • Experience with end-to-end software lifecycle, release packaging, and CI/CD pipelines
  • Strong collaborative and interpersonal skills; ability to guide and influence globally distributed teams
  • Experience designing multi-agent systems and 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
  • Experience working with AI coding agents

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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