Principal Engineer, Engineering AI Productivity
Confluent
- Pay
- $285k–$342k
- Workplace
- Remote
- Location
- Remote, United States · United States
- First seen
- 6 days ago
- Last seen
- 1 hour ago
- Board
- Ashby
Summary
We’re not just building better tech. We’re rewriting how data moves and what the world can do with it.
- react
Posting
We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them. It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together. One Confluent. One Team. One Data Streaming Platform. 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