Known — Strategy and Operations

Type: Full-time | On-site | Cow Hollow, San Francisco, CA Compensation: $80,000–$110,000 + competitive equity Hiring count: 1 via Contrario (company is hiring 2–3 total across its GTM team) Visa sponsorship: None available — candidate must be authorized to work in the US without sponsorship now or in the future Reports to: Not specified

Known is a matchmaker that talks to users and supports them like a friend, applying general intelligence to human connection. New users join by telling Known their life story — on average talking to its AI voice agent for 27 minutes — which gives uniquely intimate context that powers its matchmaking. The broader mission is to be the generational companion for relationships of all kinds: dating, friendships, networking, and beyond. Under the hood it's a personalized voice-AI system with a full data pipeline (STT and sentiment ingestion, an in-house LLM for compatibility and dynamic introductions, and agentic chat with integrations like reservations, Uber, and calendar). The team is made up of engineers who've built some of the most widely used AI-driven consumer products, including Uber Eats, Uber, and Afterpay.

Founded: 2025 | Team size: 1–10 (Seed) | Total funding: $10M seed Industry: AI Tools / consumer AI Website: knowndating.com Office: Cow Hollow, San Francisco (in person)

Backing: $10M seed led by Eurie Kim and Kirsten Green at Forerunner Ventures (the investors behind Decagon, Faire, and Oura), with NFX and PearVC. Covered by TechCrunch and the New York Times.

• Real ownership, early: You'd own a genuine piece of Known's growth and help decide the bets — shaping how the brand shows up to millions of people.
• Direct founder exposure: Small (~6-person) GTM team with direct access to founders, engineering, and investors.
• Strong backing and momentum: $10M seed from Forerunner, NFX, and PearVC, sprinting from seed toward a US-wide launch.

Known has a roughly six-person GTM team and is dialing in growth at scale across in-person events, digital, and pop-ups. This is a high-ownership seat for an operator who can decide which bets to take, build the playbooks, and execute them — explicitly not a "try whatever" role, a pure execution seat, or a pure playbook-creator seat.

• →Own a meaningful piece of Known's growth end to end: identifying the bets worth taking, building playbooks, and executing
• →Drive 0–1 GTM strategy to scale Known toward 100,000 users and a US-wide launch
• →Run growth experimentation across in-person events, digital, and pop-ups, dialed in at scale
• →Optionally, source and hire for the founding team
• →Work directly with founders and engineering to implement user feedback

Tech stack: N/A — operations / GTM role

• 1-4 years of experience in early-stage startups, consulting, investment banking, or similar high-performance environment
• Systems-minded operator who embraces ambiguity
• Strong written and verbal communication skills
• Own a piece of Known's growth
• SF Cow Hollow, in person

• High-slope operators who own things end to end and figure out the right bets themselves
• Startup, consulting, or IB backgrounds from high-performance environments
• Systems thinkers comfortable with ambiguity
• GTM/growth, recruiting, or user-feedback-implementation experience
• Background with widely used AI-driven consumer products

• No startup experience
• Weak communication skills
• Pure "execution monkey" or pure "playbook creator" profiles who can't do both
• Needs assigned, fully-scoped projects rather than owning ambiguous ones

• Salary — $80,000–$110,000
• Equity — Competitive equity
• On-site policy — In person, Cow Hollow, San Francisco (relocation supported)
• Visa sponsorship — None available
• Employment type — Full-time
• Location — Cow Hollow, San Francisco, CA

The Contrario form asks three questions beyond Additional Notes:

1. Contact
2. LinkedIn URL
3. Will you now or in the future require sponsorship (e.g., a work visa) to work in the United States?

No separate screening-call questions were provided on the role page.

Stage 1 — Intro Call — Initial conversation. Stage 2 — Technical Round 1 — First evaluation round. Stage 3 — Onsite (Technical Round 2 & Founders Chat) — Onsite combining a second evaluation round with a founders conversation. Stage 4 — Offer Extended Stage 5 — Candidate Hired — Candidate accepts and starts.

(Contrario platform pipeline stages "Pending Approval," "New Lead," and "Application Review" precede these and are not real interview stages.)

No dedicated ideal-companies list was provided on the role page. Background signals (from Green Flags): early-stage startups, consulting, and investment banking; GTM/growth, recruiting, or user-feedback work; and teams behind widely used AI-driven consumer products.

For reference only — do not source these specific profiles. Contrario labels these "Ideal Candidates — DO NOT CONTACT."

• Pere Cavallé — LinkedIn (URL not exposed on the page)
• Côme Chabaille d'Auvigny — LinkedIn (URL not exposed on the page)
• Ebhan King — LinkedIn (URL not exposed on the page)