Staff+ Software Engineer - Backend

ResolveAI•San Francisco, CA

6d•Onsite

About The Position

Resolve AI is solving the problem of software maintenance and production troubleshooting, which significantly impacts engineering velocity. We are building a transformative, autonomous AI Production Engineer designed to investigate and fix complex system issues end-to-end. Our founders, who were instrumental in creating OpenTelemetry and led Splunk Observability, have a strong track record with successful exits to Splunk and VMware. We have secured over $190M in funding from prominent investors and notable figures in the tech industry. Joining Resolve AI at this stage presents a unique opportunity to work at an AI-native company that is redefining the future of engineering work.

Requirements

Ideally with 1+ years operating at a Staff or equivalent technical leadership level.
Strong backend engineering experience in building and deploying scalable, high-performance services in high-concurrency production environments.
Experience with cloud platforms (especially AWS) and Kubernetes.
Solid understanding of databases and messaging systems for cloud-native applications.
Bias for action: ability to quickly get initial versions to users and iterate based on feedback.
Willingness to delve into technical details, debug complex problems, analyze data, and get hands-on.
Proficiency in using AI tools to enhance productivity and eagerness to explore LLM-powered systems.

Nice To Haves

Prior SRE, on-call, or incident response experience.
Familiarity with observability tools and the internals of developer-facing tools.

Responsibilities

Build simulation environments for training and evaluating AI agents on realistic SRE tasks, including debugging, incident response, infrastructure changes, and on-call duties.
Collaborate with Research Scientists and domain experts to translate real-world SRE scenarios into reproducible and challenging graded environments.
Take ownership of the architecture and implementation of major subsystems, from initial design through ongoing evolution, including infrastructure, tooling, data pipelines, and scoring.
Design, build, and scale backend services and APIs for generating, running, and scoring scenarios in high-concurrency environments.
Ensure reliability, scalability, and performance are integrated into every system layer, with a particular focus on distributed systems.
Iteratively develop and refine systems by shipping early versions, monitoring performance, identifying issues, and making improvements.
Focus on the realism of environments, ensuring they accurately reflect production failures rather than sanitized versions.
Leverage AI tools across the entire stack, including code generation, scenario generation, and debugging, to enhance productivity.