Confluent - Staff Software Engineer - Stream Processing & Analytics

IBM; Lowell (MA); On-site; USD 150,000 - 230,000; Full time

Job summary

IBM is seeking an experienced backend engineer to help build Confluent Cloud AI capabilities, delivering real-time data processing and inference on streaming data within a cloud-native platform.

You will own end-to-end features, collaborate across teams, and design scalable services in Go, Java, and Python, with Kubernetes and distributed systems at the core.

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.
• 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.

Responsibilities

• 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.
• 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.

Skills

Distributed systems design

Kubernetes

Go/Java/Python

Cross-team leadership

Communication

Education

Master's Degree

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.

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

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.

About the Role:

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.

Preferred Education

Master's Degree

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.