Member of Technical Staff, Applied AI

**GC AI** Member of Technical Staff, Applied AI; $180K–$430K + equity; US/Canada (Remote, Hybrid Tue–Thu near hubs)

**About Company** GC AI is the fastest-growing legal AI platform for in-house legal teams, helping lawyers draft, review, and analyze legal documents in seconds with accuracy built for real legal work. More than 1,800 companies use GC AI, including 150+ public companies and 25+ unicorns — brands like News Corp, Miro, Bass Pro Shops, Snyk, Skims, Liquid Death, Vercel, Zscaler, and TIME. The product carries an NPS of 70-75 and recently won a #1 SaaS customer satisfaction award; sales is ahead of plan and the company is on track for a Series C.

GC AI raised a $60M Series B in November 2025 at a $555M valuation, led by Scale Venture Partners and Northzone, with Guillermo Rauch (CEO of Vercel) among the strategic investors. Co-founder and CEO Cecilia Ziniti is a 20-year legal veteran who was a founding lawyer at Amazon Alexa, then Cruise, then Replit — where she met co-founder and CTO Bardia Pourvakil and became focused on AI. About 20% of the company are lawyers, forming an R&D function that bakes legal expertise directly into the product (including attorneys who submit pull requests reviewed and shipped under engineering supervision).

The engineering team is under 20 people and doubling this year. Culture is high-performance and AI-native (the team builds with tools like Claude Code), with strong pay and equity for people who perform. The team is distributed across the US and Canada, intentionally coming together for 3-4 engineering offsites plus a company offsite each year; those within ~50 miles of the San Mateo, CA or Provo, UT hubs work in-office Tuesday-Thursday.

**About the Role** GC AI is building out its Applied AI team, targeting 5 engineers. This is a full-stack engineering role with a strong AI execution layer — not a machine learning or data science seat. You'll architect and drive GC AI's core AI features end to end, from concept to production, with heavy evaluation work every time a new model ships (the team runs 4-5 models tuned for different tasks) and build the frameworks that make rapid prototyping possible as new models release weekly.

**Responsibilities** - Architect and ship LLM orchestration and RAG features from concept to production. - Run evaluation and testing work on every model release across the 4-5 models GC AI uses, tuned per task. - Integrate LLM capabilities, AI tools, and connectors into the product. - Build repeatable frameworks for rapid prototyping as new models release on a weekly cadence. - Partner directly with R&D attorneys who submit pull requests, reviewing and shipping their code under engineering supervision. - Mentor other engineers as the Applied AI team scales.

**Required Skills** A. Strong full-stack or specialized front/back-end engineering background at a strong product company (enterprise or consumer) — ideally with startup-scale ownership, not exclusively large-company experience. B. Deep, hands-on TypeScript/JavaScript and React exposure — this can't be the first time picking up the tools. C. Real AI exposure — has built AI products, chatbots, or LLM integrations (internal tools count) and is "AI-native" day to day. D. Not a deep ML/research background — GC AI is explicit this is a shipping role, not a machine-learning or data-science seat.

**Bonus Skills** - Legal domain or complex text/document processing experience (a nice-to-have, not required — strong engineering matters most). - Founding engineer experience, especially with a notable exit/acquisition. - Retrieval-augmented generation (RAG) systems experience. - Multi-agent AI systems background.

**Logistical Info** - Location: Remote across the US and Canada. Hybrid — Tuesday, Wednesday, and Thursday in-office — for anyone within ~50 miles of the San Mateo, CA or Provo, UT hub offices. - Compensation: $180K–$430K + equity. - Number of openings: 5. - **Other:** H-1B transfers supported; no new visa sponsorship.

**Ideal Background** - Target companies: Notion, Ramp, Stripe, Meta, Amazon, Apollo, HeyGen, Harvey, Ironclad, Airbnb, and comparable strong enterprise or consumer product companies; candidates who scaled at a big company (e.g. Facebook, Amazon) and then moved to a smaller startup and took real ownership are a strong pattern. - Legal-AI competitor pedigree is generally not a draw here (Wordsmith, Spellbook, Legora) — the main exceptions the hiring manager called out are Harvey and Ironclad. - Founding-engineer experience with a strong exit (e.g., an acquisition by a company like Stripe) is one of the strongest signals seen in calibration. - A law degree or legal background is a nice-to-have, not a requirement — strong engineering is still the core bar. - Priority: this is GC AI's single highest-priority hire company-wide.

**Green Flags** - Founders, founding engineers, and evidence of rapid promotion or "extraordinary ability." - AI-native mindset and genuine excitement about building AI products, even if not obvious from a resume.

**Red Flags** - A pattern of short job stints (one short stint isn't disqualifying; a repeated pattern is). - Deep ML/research background without strong TypeScript/React and product experience. - Fraud pattern: watch for candidates citing the same employer as other suspicious profiles (e.g., "Abridge"), VOIP/burner phone numbers (e.g., Sinch), AI-generated LinkedIn photos, and insistence on remote-only roles