Job Description
A Software Engineer in GenAI Infrastructure Agent Systems at Nuro will design and develop platforms and tools to enhance AI agent performance, automate ML research, and improve developer productivity within autonomous driving and AI-powered engineering workflows.
Key Responsibilities
- Design and build AI agent infrastructure, including orchestration, sandboxing, and isolation systems
- Develop skill plugin frameworks and integrate internal tools such as CI/CD, code, and observability systems
- Scale compute infrastructure for agent workloads using GCP, Kubernetes
- Build autoresearch systems to run experiments, evaluate results, and improve ML models
- Implement memory, feedback loops, and long-horizon reasoning for self-improving agents
- Create AI-powered engineering tools for support, triage, workflow automation, code generation, debugging, testing, and PR review
- Design evaluation and observability systems for agent performance and reliability
- Integrate agents into CI/CD pipelines for testing, failure attribution, and remediation
Requirements
- At least 4 years of industry experience in software engineering.
- Bachelor's degree (BS) or Master's degree (MS) in Computer Science or equivalent practical experience.
- Strong programming skills in Python, C++, or Go, with experience building scalable, reliable systems.
- Solid background in cloud infrastructure including GCP, AWS, Kubernetes, CI/CD, and developer tooling.
- Experience designing and building AI agent infrastructure, including agent orchestration, sandboxing, and isolation systems.
- Experience developing skill plugin frameworks and integrating internal tools such as CI/CD, code, and observability systems.
- Experience scaling compute infrastructure for agent workloads using GCP and Kubernetes.
- Experience building autoresearch systems that run experiments, evaluate results, and propose improvements to core ML models, including implementing memory, feedback loops, and long-horizon reasoning.
- Experience integrating systems with ML training, evaluation, and data pipelines.
- Experience developing AI-powered engineering tools such as assistants for support, triage, workflow automation, code generation, debugging, testing, and pull request review.
- Ability to detect and resolve performance and reliability issues automatically.
- Ability to design evaluation and observability systems for agent performance.
- Experience integrating agents into CI/CD pipelines for testing, failure attribution, and remediation.
- Experience building knowledge systems for search, retrieval, and reuse.
- Strong systems thinking across infrastructure, memory, and tooling, with the ability to work end-to-end.
- Interest in autonomous, self-improving systems and ML-driven workflows.
- Passion for building production-grade AI agent systems and improving engineering efficiency through automation.
Benefits & Perks
Compensation/salary range between $160,360 and $240,540 depending on experience and qualifications
Annual performance bonus
Equity in the company
Competitive benefits package
Ready to Apply?
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