Staff Software Engineer

confluent

Mountain View (NY)

On-site

USD 180,000 - 260,000

Full time

14 days+

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Job summary

Confluent is seeking an experienced engineer to help build Confluent Cloud's AI capabilities—enabling AI and agents to run in-place on real-time streaming data.

You will own substantial features across multiple services, guiding design decisions that span user APIs, model lifecycle, and the serving layer, collaborating with teams to align on approach and outcomes.

Qualifications

  • 10+ years of experience designing, building, and operating distributed systems or cloud-native backend infrastructure.
  • Strong working knowledge of Kubernetes and distributed-systems patterns.
  • Proficiency in Go, Java, or Python, with willingness to work across all three.
  • Track record of leading cross-team technical work and rallying stakeholders.
  • Excellent written and verbal communication, capable of drafting designs for non-reporting teams.

Responsibilities

  • Design and build backend services that run AI and model inference on real-time data.
  • Own features end to end—from design to rollout—across multiple services.
  • Make cross-team technical decisions on model lifecycle, inference routing, and agent execution.
  • Ensure production-grade quality, including test coverage and operability.
  • Mentor engineers and participate in on-call for the services owned by the team.

Skills

Go
Java
Python
Kubernetes
Distributed systems
Cross-team leadership

Job description

We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them.

It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together.

One Confluent. One Team. One Data Streaming Platform.

About the Role:

You’ll help build Confluent Cloud's AI capabilities — the layer that lets customers bring AI and AI agents capabilities directly to their real-time data. Instead of moving data out to a separate system to run inference or build an agent, our customers do it in place, on streaming data, as part of the same platform they already use to move and process events at scale.

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.

What You Will Do:
  • 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.

What You Will Bring:
  • 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.

What Gives You an Edge:
  • Exposure to model serving, LLM/agent infrastructure, or streaming data systems.

    • 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.

Ready to build what's next? Let’s get in motion.
Come As You Are

Belonging isn’t a perk here. It’s the baseline. We work across time zones and backgrounds, knowing the best ideas come from different perspectives. And we make space for everyone to lead, grow, and challenge what’s possible.

We’re proud to be an equal opportunity workplace. Employment decisions are based on job-related criteria, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by law.

Privacy Statement

Confluent is an IBM subsidiary which has been acquired by IBM and will be integrated into the IBM organization. By proceeding with this application, you understand that Confluent will share your personal information with other IBM affiliates involved in your recruitment process, wherever these are located. More Information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here.

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