Product Manager / Sr. Product Manager

Translucent•New York, NY

3h•$150,000 - $220,000•Hybrid

About The Position

Healthcare providers drive $2.5 trillion in medical expenditures annually — and operate on razor-thin 2–5% margins. Despite these stakes, the finance teams behind these organizations are buried in spreadsheets, manual data pulls, and disconnected systems, spending more time finding and cleaning data than actually using it to make decisions. Translucent is changing that. We're building the agentic AI platform designed exclusively for healthcare finance — giving every finance team, department, and service line their own arsenal of AI Agents that run 24/7 and understand their specific data, business logic, and workflows. Founded in 2024 and backed by GV, NEA, FPV, and Virtue, we've already been deployed by healthcare organizations managing over $5 billion in combined revenue. The product-market fit is real, the problem is massive, and we're just getting started. If you want to work at the intersection of AI and one of the most complex, consequential industries in the world — this is the place. We're hiring a Product Manager or Senior Product Manager to own products inside one of our core verticals — e.g. Revenue Intelligence, Physician Enterprise, Pharmacy, etc. We'll match the vertical to your background and interest. The role requires a PM willing to work with our customers, apply strategy, & target real economic problems to quickly ship a working product. Candidate must be capable of driving adoption for a variety of users (e.g. healthcare operators, finance team, etc.) and quantitatively track the dollar value captured. Less roadmap authorship, more shipped software in customers' hands. You'll work directly with the vertical's Product Lead, Deployment, AI Engineering, Design, and our delivery team — and directly with customers. There is no layer between you and the customer using what you built.

Requirements

3–5 years in product for the Product Manager level, or 5–8 years for Senior Product Manager, in B2B or enterprise SaaS
You've shipped a data-heavy, workflow-driven product that showed high customer usage — analytics, financial, or AI-powered — and can walk through how you got them to use it
Technical fluency: you write your own SQL and are comfortable working with datasets and data models.
Take an abstract product concept from a customer or the sales teams, go deep in the domain, and produce a quickly vibe-coded prototype you’d feel comfortable to present to a customer for discovery to refine it
Hands-on with AI tooling in your daily workflow, with specific examples of where it made you dramatically faster
Healthcare finance or operations exposure, or a genuine appetite to learn a hard domain fast. Access to internal SMEs allow for candidates to learn new domains in a quick and deep fashion.
Bias toward action: you take an ambiguous problem to a working V1 quickly, then iterate against real feedback
Comfortable wearing multiple hats with no ego about it: mocks, copy, QA, customer training, data cleanup – whatever the product needs
Startup realist: ready to sprint when priorities shift and jump into unfamiliar areas when the team needs it
Excellent communication across technical and non-technical audiences, including in front of customers

Nice To Haves

Any Agentic AI work or personal experience
Early startup experience
Direct experience in healthcare, specifically health system finance, revenue cycle, physician compensation, or pharmacy economics (340B, rebates, drug spend)
Familiarity with Epic (Clarity/Caboodle), Strata, Vizient, Premier, or comparable provider finance and decision-support systems
Experience designing agents, copilots, or conversational interfaces
Prior 0→1 work where you owned hands-on execution
Provider-side consulting or operating experience

Responsibilities

Own one or more products inside your vertical end to end — from problem definition through shipped software, onboarding, and measured usage
Partner closely with customers to hold discovery sessions that define what's most important to build
Write specs engineers can build from without a meeting, and prototype the thing yourself before you ask anyone to build it
Sit with healthcare finance and operations users, run onboarding and training sessions, and get every persona to first value fast
Own the numbers for your product: activation, weekly usage by persona, opportunities acted on, and dollars recovered or protected
Define what your product's agents do autonomously versus with a human in the loop, and set the eval criteria with AI Engineering. In healthcare finance, accuracy is non-negotiable
Build on shared platform capabilities — AI platform-wide capabilities, stored contracts, external datasets, the context layer, chat agents, the agent harness — rather than one-off logic per customer
Run clean intake and triage in Linear against defined SLAs, so customer-reported issues and new requests don't quietly become the roadmap
Design the missing pieces with Design — empty, loading, error, and edge-case states — and own QA against intent before anything reaches a customer
Write clearly and often: crisp updates, honest status, and the trade-offs you made