Senior Software Engineer, Agent Simulation and Evaluation

Job Title

Senior Software Engineer, Agent Simulation and Evaluation

Role Summary

Join the LPU organization to build agentic systems and engineering tools that automate simulation, evaluation, and performance analysis for AI inference workloads across GPU and LPU platforms. The role focuses on performance modeling, validating simulation fidelity, and accelerating engineering decisions.

Experience Level

Senior-level. Typically requires 5+ years of software development experience, including at least 2 years building AI agents or AI-backed engineering systems.

Responsibilities

Primary responsibilities include:

• 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-ups.
• 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.
• Collaborate with inference, hardware, runtime, compiler, evaluation, and product teams to improve simulation fidelity and accelerate decisions.
• Automate benchmarking, workload characterization, capacity planning, and release qualification workflows for LPU.

Requirements

Must-have skills and experience:

• Strong 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.
• Proficient in Python and experienced in building reliable engineering tools.
• 5+ years of relevant software development experience.
• At least 2 years specifically building AI agents or AI-backed engineering systems.
• Strong analytical approach to experimentation, data collection, and validation.
• Nice-to-have: knowledge of GPU/accelerator architecture, distributed inference, high-performance computing, or open-source projects demonstrating agentic AI or performance engineering.

Education Requirements

MS in Computer Science, Engineering, or a related technical field preferred; equivalent practical experience accepted.

Compensation note: base salary ranges provided in the source (varies by level and location); equity and benefits are also available. Applications will be accepted at least until 2026-08-16.

NVIDIA is an equal opportunity employer.

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.