Confluent - Staff Software Engineer - Stream Processing & Analytics

IBM Computing; Seattle (WA); On-site; USD 180,000 - 260,000; Full time

Job summary

IBM Software is seeking an experienced backend engineer to help build Confluent Cloud's AI capabilities, enabling in-place inference on real-time streaming data. You will own end-to-end features across services, make cross-team technical decisions, and ensure code quality and operability for production systems.

The role requires 10+ years of distributed systems experience, strong Kubernetes knowledge, and proficiency in Go, Java, or Python, with a track record of leading cross-team initiatives.

Qualifications

• 10+ years designing, building, and operating distributed systems in production.
• Strong working knowledge of Kubernetes and distributed-systems patterns.
• Proficiency in at least one of Go, Java, or Python, and willingness to work across all three.
• Track record of leading cross-team technical work and rallying stakeholders.
• Excellent written and verbal communication, able to write a design doc that aligns diverse teams.

Responsibilities

• Design and build the backend services that run AI and model inference on real-time data.
• Own features end to end—from design to rollout and governance.
• Make technical calls on systems spanning multiple teams: model lifecycle, inference routing, and agent execution.
• Ensure quality across code, tests, documentation, and operability for production readiness.
• Mentor engineers and lead code reviews to raise team performance.
• Participate in on-call for the services you own, maintaining healthy team processes.

Skills

Go

Java

Python

Kubernetes

Distributed systems

Job description

Introduction

At IBM Software, we transform client challenges into solutions. Building the world’s leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You’ll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM’s product and technology landscape. Here, you’ll have the tools and opportunities to advance your career while creating software that changes the world.

Your role and responsibilities

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.

Required technical and professional expertise

• 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.

Preferred technical and professional experience

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.

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.