Principal Engineer, Engineering AI Productivity

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.

Responsibilities

• 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.
• 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.
• 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.

Requirements

• 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).

Qualifications

• 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.