Senior Software Engineer, Agent Simulation and Evaluation

Job Title

Senior Software Engineer, Agent Simulation and Evaluation

Role Summary

Work within the LPU organization to build agentic systems that automate simulation, evaluation, performance analysis, and engineering workflows across GPU and LPU platforms. The role blends model-architecture knowledge with performance engineering to improve evaluation fidelity and accelerate hardware and software decisions.

Experience Level

Senior — 5+ years of relevant software development experience; at least 2 years building AI agents or AI-backed engineering systems.

Responsibilities

Primary responsibilities include designing, implementing, and automating evaluation and simulation pipelines:

• Design and implement agentic systems that automate simulation, evaluation, performance analysis, and reporting.
• Develop tools to configure experiments, run evaluations, analyze results, detect regressions, and recommend follow-up work.
• Analyze inference characteristics of LLMs, reasoning models, coding agents, multimodal models, and agentic harnesses.
• Build and validate performance models for GPU, LPU, and heterogeneous GPU–LPU systems.
• Automate benchmarking, workload characterization, capacity planning, and release qualification workflows.
• Collaborate with inference, hardware, runtime, compiler, evaluation, and product teams to improve simulation quality and accelerate engineering decisions.

Requirements

Must-have skills and experience:

• Proven experience building AI agents or AI-backed engineering systems.
• Familiarity with modern model architectures and AI inference workloads.
• Experience evaluating AI models or agents and analyzing performance.
• Experience with simulation, profiling, benchmarking, or performance modeling.
• Strong Python skills and experience building reliable engineering tools.
• 5+ years of relevant software development experience; 2+ years building AI agents or similar systems.

Nice-to-have:

• Experience using coding agents (for example, Codex or Claude Code) to automate technical workflows.
• Knowledge of GPU/accelerator architecture, distributed inference, or high-performance computing.
• Open-source projects demonstrating agentic AI, evaluation, or performance-engineering applications.
• A rigorous analytical approach to experimentation, data collection, and validation.

Education Requirements

MS in Computer Science, Engineering, or a related field, or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.