Staff Software Engineer, Confluent

• 10+ years of significant experience designing, building, and operating distributed systems or cloud-native backend infrastructure in production
• .Strong working knowledge of Kubernetes and distributed-systems patterns (control loops, API servers, high-scale control planes), plus the fundamentals — containerization, networking, resource isolation
• Proficiency in at least one of Go, Java, or Python, and the willingness to work across all three
• A track record of leading cross-team technical work: turning ambiguous requirements into designs others can rally behind
• Excellent written and verbal communication — you can write a design doc that aligns people who don't report to you
• You don't need a background in ML research or model training — this role is about building and operating the platform that serves AI reliably at scale, not inventing the models

Desirable

• As an engineer, you'll own delivery of significant pieces of this product — not just writing code, but deciding how a capability should work across the services that make it up
• The interesting problems here rarely live in one place: shipping something like inference-on-streaming-data or an AI agent that reacts to live events touches several systems at once — the user-facing API, the services that manage model and agent lifecycle, the control plane that schedules and runs the work, and the serving layer that actually executes inference
• You'll be expected to reason across those boundaries, make sound design calls, and get engineers inside and outside the team aligned on the approach
• Design and build the backend services (primarily Go, Java, and Python) that run AI and model inference on real-time data
• Own features end to end — drafting the design, aligning stakeholders inside and outside the team, and driving the decision to a conclusion
• Make the technical calls on systems that span teams: model lifecycle, inference routing, and agent execution
• Own the quality of what you ship — code, test coverage, documentation, operability, and rollout safety. This is production infrastructure serving live inference, so reliability isn't an afterthought
• Make the engineers around you better through code review, design feedback, and being someone the team trusts with ambiguous, cross-cutting work
• Participate in on-call for the services your team owns, and help keep the team's processes and rituals healthy