Staff Product Operations Manager

Confluent Confluent · Data AI · United States · Remote · Product

This role is for a Staff Product Operations Manager who will serve as the product manager for Confluent's Product Development Lifecycle (PDLC). The core responsibility is to own the improvement roadmap, build and ship AI-integrated workflows, and iterate based on feedback. The role involves translating strategy into working workflows, building tooling and templates, and running the system day-to-day, with a focus on driving adoption of these AI-enhanced processes among product managers.

What you'd actually do

  1. Take the vision for a modernized, AI-integrated Product Development Lifecycle and make it real. This means implementing AI-driven workflows at every stage — from discovery and customer synthesis through spec, review, and launch — and owning the ongoing iteration that keeps the system current and credible.
  2. Turn the design into a working system. This role owns implementation — not just the blueprint. You will roll out new workflows, build and test the tooling and templates that support them, collect PM feedback, and continuously improve. Think of the PDLC as a product in permanent beta.
  3. Own the canonical frameworks and templates for core product artifacts: PRFAQ, PRD, NPI, and the rituals that surround them. Keep them current and credible — PMs should see these as genuinely useful, not bureaucratic overhead.
  4. Translate product strategy and leadership intent into working processes PMs actually adopt. You will be the connective tissue between what leadership wants to happen and what actually happens on the ground.
  5. Design and lead rollout of every new process. PMs are high-autonomy, skeptical of top-down mandates, and time-constrained. Your job is to earn adoption through empathy, clarity, and demonstrated value, rather than enforcement.

Skills

Required

  • 8+ years in Product Management, Product Operations, or a closely related role
  • demonstrated experience operating at the intersection of product thinking and process design
  • Hands-on PM experience
  • shipped product
  • Systems thinking at the process layer
  • Meaningful AI fluency
  • thought deeply about how AI changes the product development process
  • design workflows that use AI as infrastructure
  • A track record of driving adoption in high-autonomy orgs
  • Strong written communication

What the JD emphasized

  • AI-integrated Product Development Lifecycle
  • AI-driven workflows
  • AI as infrastructure
  • shipped product
  • PMs are high-autonomy, skeptical of top-down mandates, and time-constrained
  • convince skeptical, senior PMs to change how they work

Other signals

  • AI-integrated Product Development Lifecycle
  • implementing AI-driven workflows
  • design workflows that use AI as infrastructure