Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Go @ 4
Kubernetes @ 7
Python @ 4
Java @ 4
Distributed Systems @ 8
Machine Learning @ 6
Communication @ 4
Networking @ 7
React @ 4
API @ 4
HTTP @ 4
LLM @ 4
AI @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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.
Role overview
You'll help build Confluent Cloud's AI capabilities — the layer that lets customers bring machine learning and AI agents 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. Shipping features such as 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.
Responsibilities
- Design and build 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.
Requirements
- 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.
Culture & privacy
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. 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.
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 at: http://ibm.com/careers/us-en/privacy-policy/