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# Senior Software Engineer, Open Harness Engineering

- **Company:** NVIDIA Corporation
- **Location:** Denver, CO, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Code Review, Software Debugging, Programming Tools, Monitoring of Systems, Python (Programming Language), Open Source Technology, Regression Testing, Software Engineering, Software Systems, TypeScript, Graphics Processing Unit (GPU), Large Language Models, Reliability of Systems, AI Coding Agents, Agentic-AI, Information Technology, Free and Open-Source Software, Api Design
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-open-harness-engineering-denver-co--b5e5a10c-a06c-40c7-ac58-f032044fbb25

## About the Role

Software Engineering, Autonomous Driving Systems, GPU (Graphics Processing Unit), Artificial Intelligence (AI), Software Engineering, Identify Issues, Programming Tools, Artificial Intelligence (AI) Agents, Benchmarking, Team Building, * Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Applied Math, or a related field, or equivalent experience.

 * 8+ years of hands-on software-engineering experience, with demonstrated technical ownership of production systems; and architecture design leadership.
 * Expert Python skills and working proficiency in Rust, Go, C++, or TypeScript, with the ability to debug systems across language and process boundaries.
 * Experience building or extending LLM agents, coding agents, tool-use loops, model-provider integrations, developer tools, or evaluation infrastructure.
 * Solid understanding of asynchronous execution, subprocesses, containers, sandboxing, callbacks, retries, networking, and distributed compute.
 * Experience crafting reproducible experiments, benchmark methodology, performance investigations, regression gates, or reliability analysis under nondeterministic conditions.
 * A record of shipping and maintaining open-source or developer-facing software with sound testing, API development, documentation, and code reviews.

Ways to stand out from the crowd

 * Meaningful contributions to open-source coding agents, harnesses, agent runtimes, evaluation frameworks, developer tools, or observability projects.
 * Published research, technical writing, patents, or substantive open-source work in autonomous software engineering, agent evaluation, reliability, tool use, or inference efficiency.
 * Experience with SWE-bench, Terminal-Bench, AgentBench, or comparable public agent benchmarks.
 * Shipped improvements to context management, tool interfaces, retries, sandboxed repository execution, long-running agent loops, or evaluation environments.
 * Experience with trace-analysis and observability systems such as OpenTelemetry, OpenInference, structured event pipelines, exporters, or debugging tools.

## Description

Are you excited about open-source software, developer tools, and the future of agentic applications? We are looking for a Senior Software Engineer to help build the core libraries, evaluation systems, and reusable harness capabilities that make AI agents safer, faster, and easier for developers to trust. In this role, you will work hands-on across open-source agent harnesses, sandboxed execution, model-provider infrastructure, and agent benchmarks to help improve the next generation of agents. You will turn agent-evaluation evidence into real improvements: diagnosing failures, contributing upstream, and proving quality, reliability, cost, and latency gains across models. Join our creative engineering team building foundational technology for the future wave of autonomous software systems!

What you'll be doing:

 * Define and evolve the technical approach for evaluating and improving open agent harnesses across frameworks, models, and benchmark environments.
 * Build and operate scalable, reproducible evaluation systems spanning CI, scheduled compute, sandboxed execution, artifact provenance, trace capture, and analysis.
 * Diagnose agent failures from traces, logs, tool results, and benchmark artifacts, separating harness, evaluator, environment, inference, and model causes.
 * Design controlled experiments and promotion criteria that distinguish genuine harness improvements from noise, benchmark artifacts, or model-specific gains.
 * Ship focused harness and runtime improvements, including upstream open-source contributions, detectors, regression tests, and maintainable documentation.
 * Partner with Relay, Hermes, model, infrastructure, and research teams to turn recurring optimization needs into reusable runtime, trace, and evaluation capabilities.