Product Operations Manager, AI & Systems
Builds and evolves AI-powered workflows, tooling, and knowledge systems to streamline product organization operations across planning, building, and scaling. Partners with Product, Engineering, and GTM teams; requires 5+ years in product ops or management with strong AI fluency.
About the job
Responsibilities
- Own and evolve the product development lifecycle as a system – using AI to diagnose breakdowns, redesign workflows, and continuously improve how we build
- Build AI-powered workflows that reduce the administrative layer of product work – including spec-to-GTM translation, synthesis of customer signals, QA scenario generation, and automated progress reporting
- Build and maintain the product organization’s knowledge layer and sources of truth – including roadmap data, decision logs, and project status – structured for both human and AI consumption
- Own and evolve the product tooling ecosystem – driving consistency, standardization, and thoughtful adoption across teams
- Drive adoption, enablement, and upskilling across the Product organization – ensuring teams effectively use the systems, tools, and AI workflows you build
- Scale what works – identify high-impact workflows and patterns emerging within teams and turn them into shared standards through tooling, documentation, and enablement
- Own PM hiring infrastructure and product ops metrics – including hiring design and onboarding, and defining and tracking the metrics that inform product leadership decisions
What you'll need
- 5+ years in product operations, product management, strategy/operations, or a related role — with a track record of building systems and tooling, not just managing processes
- Deep fluency with AI as a core part of your workflow — you use it instinctively in your own work and know how to design systems that meaningfully leverage it
- Strong product judgment applied internally — you approach operational problems with the same rigor as customer-facing ones, with a bias toward simple, scalable solutions
- High data fluency — able to define meaningful metrics, instrument systems, and translate insights into action
- Strong systems thinking — you can distinguish between process issues and structural problems, and know when to optimize vs redesign
- Clear, direct communication — able to surface what’s working and what isn’t, and influence across teams, including senior leadership
Nice to have
- Experience building or scaling a product organization’s operating system (e.g., PDLC, knowledge management, tooling, hiring, onboarding)
- Experience in a high-growth environment, ideally within a regulated domain (fintech, healthcare, HR tech)
Compensation
The base wage range for this position based in our New York City Office is targeted at $127,000.00 to $173,300.00 per year.
Skills
AI, Product Development Lifecycle, Pdlc, Workflow Automation, Knowledge Management, Roadmapping, Tooling, Metrics Tracking, Data Analysis, Systems Thinking
Similar jobs
Product Operations jobsProduct Operations Specialist partnering with Bill Pay team to reduce customer friction in accounts payable workflows. Own voice-of-customer feedback loops, translate insights into product requirements, own feature launches, and directly ship UX improvements using AI tools.
Own federal and state tax updates for Cash App’s tax software, translating tax-law changes into product requirements, code updates, testing, and launches. The role requires tax software experience, strong organization, code literacy, and a related bachelor’s degree.
Leads cross-functional customer experience and operations programs that identify member and agent friction, improve support processes, and ensure operational readiness for product and policy changes. Requires 5+ years of program leadership, strong analytics, regulated-environment experience, and stakeholder influence.
Own recovery operations for an AI product serving enterprise CPG brands, using SQL and operational analysis to improve deduction outcomes, guide product requirements, and communicate performance to customers. The role requires 4+ years in product operations, analytics, revenue operations, consulting, or a similar data-heavy function.
Own operational delivery for Mercor’s research partnerships, including benchmark prioritization, evaluation and post-training engagements, vendor capacity, budgets, and customer delivery. The role requires technical fluency in LLM evaluation and post-training, plus strong cross-functional execution and communication.