Senior Software Engineer - Confluent Applied AI for DevProd

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. With Confluent, data doesn’t sit still. We put information in motion, streaming in near real time so organizations can react faster, build smarter, and deliver experiences as dynamic as the world around them. Your role and responsibilities Engineers in the Developer Productivity team build applied AI systems to improve how Confluent engineers design, implement, review, test, document, and operate software.

You will turn AI into reliable engineering workflows for AI-automated implementation, developer toil reduction, PR review, documentation generation, and CI guardrails.

As a Senior Engineer, you will own these workflows end-to-end: identifying pain points, designing AI-enabled solutions, shipping to production, measuring impact, and iterating until they become trusted, paved paths.

You will partner with product, platform, and infrastructure teams to make AI-assisted workflows the default standard at Confluent. What You Will Do Design and operate AI-assisted workflows for code review, ticket-to-PR flows, documentation, and CI/CD guardrails. Own projects end-to-end: from definition and design to implementation, rollout, and optimization. Build backend services and orchestration layers connecting LLMs to developer systems (GitHub, Jira, Slack, CI, and internal platforms). Translate ambiguous engineering challenges into practical, opinionated products that improve developer velocity and quality. Collaborate with platform teams to integrate AI workflows into standard runtimes, managed workloads, and deployment paths. Implement robust safety and governance, including access control, policy enforcement, and observability. Use data-driven metrics—adoption, reliability, and cost—to guide product iterations rather than anecdotal feedback. Maintain high engineering standards through clean, well-tested code and thoughtful design reviews. This position can be performed from anywhere in the US. - Experience building and operating backend production systems. - Proficiency in at least one major language (e.g., Java, Go, Python). - Experience building internal developer-facing platforms or workflow automation tools. - Hands-on experience applying LLM techniques to software engineering workflows; ability to build reliable systems beyond generic prompting. - Experience with cloud-native infrastructure, including containers and Kubernetes. - Strong judgment on software quality, testing strategies, and operational guardrails. - Product mindset: focus on user adoption, time-saving, and quality improvements - Effective collaboration skills across cross-functional boundaries. - Experience building AI-assisted workflows for code review, test generation, incident response, or developer onboarding. - Integrating systems with developer tools (source control, CI, issue trackers, chat tools, internal portals). - Familiarity with platform foundations like service runtimes, progressive delivery, and configuration systems. - Expertise in distributed systems, developer productivity, or infrastructure-heavy environments. - Experience creating opinionated paved paths and governance models. United States Software Engineering Hybrid Professional Multiple Cities