Confluent - Principal Engineer - AI Productivity

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. About the Role: We’re seeking a strategic and hands-on technical leader to define and drive Confluent’s internal agentic AI capabilities, and adoption of smart, automated decisioning systems for R&D productivity. In this role, you will partner across Engineering, Security, and IT to scale AI usage across our platform to accelerate value for customers and the business. You will operationalize a vision where AI augments developers, automates routine tasks, and orchestrates intelligent workflows that unlock new usage patterns. What You Will Do: Strategy & Vision Define and evangelize the AI and agentic flows strategy — aligning business metrics, engineering needs, and platform opportunities. Build a roadmap for introducing agentic automation features, smart assistants, and AI-driven workflows across all aspects of engineering. Identify and resolve bottlenecks across the entire product and software development life cycle. Cross-Functional Leadership Partner with Engineering, Trust and Security to integrate AI capabilities responsibly and at scale. Operationalize AI adoption internally and share use cases externally Drive complex cross-team projects requiring multi-stakeholder alignment Continuously raise the bar for code/architectural quality across engineering Execution & Delivery Lead the delivery of core agentic workflows that improves productivity across engineering Balance of hands-on contributions with effective delegation to others. Expect 60% execution and 40% strategy setting. Drive measurable adoption of AI tooling and flows with internal teams Governance & Best Practices Ability to adopt industry standards, ethical frameworks, guardrails, and quality metrics for AI behavior and automated flows. Define success metrics and KPIs (e.g., AI-driven usage lift, automation ROI, reduction in manual workflows). Thought Leadership Participate in external forums — conferences, podcasts, customer briefings on occasion Evolve as the technology landscape shifts Write internal playbooks for building and scaling agentic outcomes. If you’re someone looking to bring agentic system design to production scale, let’s talk. Technical and Product Acumen 8+ years driving strategic productivity initiatives, ideally in SaaS/Cloud platforms or developer tools with some proven experience in AI initiatives. Considered an expert in building distributed systems and/or the infrastructure and tools to support it. Leadership & Collaboration Proven ability to lead cross-functional teams and influence senior stakeholders without direct authority. Strong communicator who can translate complex technical strategies into impact-oriented outcomes. Execution Focus Demonstrated track record delivering products or features that generated measurable business value. Comfortable defining success criteria, metrics, and ROI for ambiguous, future-facing domains. AI/ML & Automation Hands-on experience with AI or adjacent AI/ML platform experience with LLM integration and workflow automation, with demonstrated appetite to build toward agentic patterns Deep understanding of responsible AI practices and governance. Customer & Business Mindset Passion for solving real customer problems with elegant, scalable solutions. Ability to tie technical efforts directly to business KPIs (adoption, retention, revenue impact). Experience working in cloud-native platforms or developer ecosystems. Prior leadership in scaling internal AI platforms or driving AI adoption across large organizations. Background in real-time data, event-driven architecture, or platform engineering. United States Software Engineering Remote Professional Multiple Cities (0147) International Business Machines Corporation