The ad says“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”
The ad says“Experience working in cloud-native platforms or developer ecosystems”
The ad says“Experience working in cloud-native platforms or developer ecosystems”
The ad says“Considered an expert in building distributed systems and/or the infrastructure and tools to support it”
The ad says“Background in real-time data, event-driven architecture, or platform engineering”
The ad says“Deep understanding of responsible AI practices and governance”
The ad says“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”
The ad says“Background in real-time data, event-driven architecture, or platform engineering”
The ad says“Background in real-time data, event-driven architecture, or platform engineering”
The ad says“Deep understanding of responsible AI practices and governance”
The ad says“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”
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
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
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
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)
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
Preferred experience
Strong communicator who can translate complex technical strategies into impact-oriented outcomes
Comfortable defining success criteria, metrics, and ROI for ambiguous, future-facing domains
Demonstrated track record delivering products or features that generated measurable business value
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
Ability to tie technical efforts directly to business KPIs (adoption, retention, revenue impact)
Proven ability to lead cross-functional teams and influence senior stakeholders without direct authority
Considered an expert in building distributed systems and/or the infrastructure and tools to support it
Passion for solving real customer problems with elegant, scalable solutions
8+ years driving strategic productivity initiatives, ideally in SaaS/Cloud platforms or developer tools with some proven experience in AI initiatives
Background in real-time data, event-driven architecture, or platform engineering
Experience working in cloud-native platforms or developer ecosystems
Prior leadership in scaling internal AI platforms or driving AI adoption across large organizations
