Senior Software Engineer, AI Infrastructure Solutions
NVIDIA is hiring a Senior Software Engineer, AI Infrastructure Solutions in Pune, India. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- Tools and skills the posting cites include OpenAI, LangChain and LangGraph.
- Level classifies it as a senior role.
- Level lists 2,700+ other open roles at NVIDIA.
- The role was posted in the last few days.
AI in this role
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. NVIDIA is seeking an outstanding Senior Software Engineer to join our AI Infrastructure Solutions team in Pune. This is your opportunity to work on groundbreaking technologies and help build the future of computing! NVIDIA is a global leader in innovation, offering a dynamic and inclusive work environment in Pune or equivalent experience. We value diversity and provide equal opportunities to all candidates. If you’re passionate about building scalable AI platforms and autonomous agent solutions that impact industries worldwide, we want to hear from you!
What You’ll Be Doing:
- Design, build, and operate AI infrastructure solutions that power LLM-based applications and autonomous agents across the enterprise.
- Develop agentic AI workflows and multi-agent systems, including tool calling, planning, memory, retrieval-augmented generation (RAG), and orchestration using frameworks such as LangChain, LangGraph, or similar.
- Integrate and serve LLMs through APIs and inference endpoints, optimizing for latency, throughput, cost, and reliability.
- Containerize applications with Docker and deploy and scale them on Kubernetes, including Helm charts, autoscaling, and GPU-enabled workloads.
- Take applications to L3 level: own production readiness, advanced troubleshooting, root-cause analysis, performance tuning, and escalation support for complex issues beyond L1/L2.
- Define and maintain observability for AI systems, including logging, metrics, tracing, and monitoring of agent behavior, LLM quality, and system health.
- Build and maintain CI/CD pipelines for automated build, test, and deployment of AI applications and infrastructure.
- Develop high-performance backend services and RESTful APIs (Python and/or .NET Core) that expose AI capabilities to internal applications.
What We Need to See:
- Bachelor’s or equivalent experience in Computer Science, Engineering, or a related field.
- 5+ years of software engineering experience, with 2+ years working on AI/LLM-based solutions.
- Hands-on experience building agentic AI and autonomous agent systems, including tool use, multi-agent orchestration, and RAG pipelines.
- Strong experience with LLMs and their integration (OpenAI-compatible APIs, NVIDIA NIM, Hugging Face, or similar), prompt engineering, and evaluation.
- Strong proficiency in Python; experience with C#/.NET Core and ASP.NET Core for REST API development is a plus.
- Solid experience with Docker and Kubernetes, including deploying, scaling, and troubleshooting containerized workloads in production.
- Proven experience supporting applications at L3 level, including incident management, debugging, performance optimization, and root-cause analysis.
- Experience with CI/CD tools (GitHub Actions, Azure DevOps, GitLab CI, Jenkins) and Git-based workflows.
Ways to Stand Out from the Crowd:
- Experience with GPU-accelerated workloads, NVIDIA AI Enterprise, NVIDIA NIM, Triton Inference Server, or NeMo.
- Familiarity with MCP (Model Context Protocol) and agent-to-agent communication patterns.
- Experience with LLM evaluation, guardrails, and safety frameworks.
- Contributions to open-source AI or infrastructure projects.
NVIDIA delivers competitive pay, a wide range of benefits, and the possibility to contribute to groundbreaking technologies. Join us in building the future of computing! 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/
How we rate this
Senior Software Engineer, AI Infrastructure Solutions at NVIDIA rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- Walk me through how you've used OpenAI in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI agents, AI Evaluation, and OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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