Software Engineer, AI Agent

Resolve AI•San Francisco, CA

About The Position

Software maintenance and production troubleshooting have become a massive tax of engineering velocity. Resolve AI is solving this by building a transformative, truly autonomous AI Production Engineer that investigates and fixes complex system issues end-to-end. Our founders (Spiros Xanthos and Mayank Agarwal) are the core creators of OpenTelemetry and led Splunk Observability. They have had 2 successful exits to Splunk and VMware. We’ve raised over $150M from top-tier investors including Lightspeed, Greylock, Unusual Ventures, and individual backers such as Jeff Dean (Chief Scientist, Google DeepMind), Thomas Dohmke (CEO, GitHub), Matt Garman (CEO, AWS), Reid Hoffman (Founder, LinkedIn), and Fei-Fei Li (Professor, Stanford). The Role We're hiring AI Agent Engineers: people who combine strong engineering fundamentals, AI-native thinking, and a relentless focus on customer outcomes. You won't just ship features. You'll own the full arc from understanding a customer's problem in production to delivering a solution that measurably improves their experience. The best software engineers have always spent more time figuring out what to build than writing the code itself. With tools like Claude Code and Cursor accelerating code authorship at an unprecedented pace, that ratio is shifting even further, and we think that's a good thing. This isn't a rebrand of the traditional software engineering role. It's a recognition that the highest-leverage engineering work today lives at the intersection of deep technical execution, customer empathy, and rigorous evaluation of what's actually working.

Requirements

4+ years of industry experience building production software, with a strong background in backend or distributed systems
Strong fundamentals in system design, data structures, and building reliable software in high concurrency environments
Experience operating systems in production, including debugging failures, performance issues, and edge cases
Hands-on experience with cloud platforms (AWS preferred), Kubernetes, and modern infrastructure tooling
Familiarity with databases, messaging systems, and service-oriented architectures
Interest in AI-driven systems, with experience or curiosity around LLM-powered applications, reasoning systems, or autonomous workflows
A strong sense of ownership and comfort working in ambiguous problem spaces
Ability to communicate clearly across technical and non-technical audiences
A builder's mindset. You enjoy shipping, iterating, and improving systems over time

Responsibilities

Own customer outcomes end to end. Work directly with customers, design partners, and internal stakeholders to define technical scope, success criteria, and delivery milestones — then build and ship the solution yourself.
Build product capabilities that matter. Design and implement features across the full stack, with a bias toward solving real problems observed in production environments rather than building in the abstract.
Integrate deeply with customer environments. Work hands-on with cloud platforms, observability systems, CI/CD pipelines, and incident response workflows to ensure our product fits seamlessly into how teams actually operate.
Diagnose and resolve complex issues. Troubleshoot hard problems across customer deployments, turning support interactions into product insights and durable fixes.
Measure what matters. Build evaluations and feedback loops that quantify customer value in a data-driven way, ensuring new capabilities are genuinely moving the needle — not just shipping.
Raise the engineering bar. Write clean, maintainable, well-tested code. Lead design discussions and code reviews. Help shape both the technical direction of the product and the engineering culture of the team.