GC AI | Member of Technical Staff, Applied AI | REMOTE (US/Canada) | $180K–$430K + equity
GC AI is building an AI platform for in-house legal teams, helping lawyers draft, review, and analyze legal documents. The product is used by 1,800+ companies, including 150+ public companies and 25+ unicorns. GC AI raised a $60M Series B in November 2025 at a $555M valuation.
We’re hiring 5 engineers for the Applied AI team.
This is a full-stack product engineering role with a strong AI execution layer — not an ML research or data science position.
We’re looking for engineers with:
- Deep, recent TypeScript/JavaScript + React production experience
- Hands-on experience shipping LLM-powered product features
- Experience with LLM orchestration, RAG, integrations, agents, and/or evaluation systems
- Strong end-to-end product ownership, from architecture through production
- A track record of shipping quickly and working closely with product
Strong signals include founding/founding-engineer experience, meaningful startup ownership, or experience scaling products at strong engineering companies before moving into a smaller high-ownership environment.
The Applied AI team also owns substantial model evaluation work as new models ship, and builds internal frameworks that allow the team to prototype and productionize new AI capabilities quickly.
Location: Remote across the US and Canada
Hybrid: Tue–Thu in-office if you’re within ~50 miles of San Mateo, CA or Provo, UT
Comp: $180K–$430K + equity
Openings: 5
Visa: H-1B transfers supported; no new visa sponsorship
Interested? Email [email protected] with the subject:
GC AI – Applied AI
Please include:
- Your LinkedIn profile
- Current location
- A short description of an AI/LLM feature you personally shipped to production
- GitHub / portfolio if relevant
the gc ai site indicates all official contact is going to have the official domains in the email. hn hiring threads are not for external recruiters to make use of. additionally its super not cool to do false representation. job stuff is stressful enough as is
AI Model Assessment Specialist | REMOTE | Contract | $22 - $70/hr
We are scaling up our AI training operations and looking to bring on a large number of contractors (up to 1,000 openings) to help evaluate, stress-test, and refine next-generation AI models.
The Role:
Essentially, high-level RLHF (Reinforcement Learning from Human Feedback) and model evaluation. You will analyze AI-generated content across various domains, fact-check complex outputs, catch subtle hallucinations, and provide detailed, constructive feedback to improve model reasoning and accuracy. You'll also simulate real-world scenarios to gauge the model's actual utility.
What we are looking for:
Native-level English (C1/C2) is a hard requirement.
Analytical Rigor: High-level reading comprehension. You need to be able to spot logical flaws, edge cases, and subtle anomalies in text.
Autonomy: Self-starters who are highly organized and can reliably manage their time in a remote setup.
Bonus: Background in research, editorial work, data annotation, or tech evaluation. We index highly on people with "good taste" and refined judgment for high-quality content.
Note: The wide hourly rate ($22 - $70/hr) reflects the variance in domain expertise, assessment complexity, and location.
Important Next Step: Please check your inbox/spam folder immediately after submitting your application. You will receive an email containing a link to an AI-driven interview. Completing this AI interview is a mandatory requirement to move your application forward.
We’re working on building production AI systems , not demos ,focused on real-world workflows, data pipelines, and integrating LLM-based systems into usable products.
Work includes:
- designing backend systems and APIs
- building and scaling LLM workflows (agents, pipelines, RAG)
- handling real-world issues like latency, reliability, and hallucination control
- integrating AI into product experiences end-to-end
Looking for engineers who:
- have built production systems (not just prototypes)
- are strong on backend design and data flow
- have experience with AI/LLM systems in real use cases
Remote, async-friendly, with some overlap with US timezones preferred.
Hi! Saw your HN post. I build exactly this: production FastAPI+LangGraph RAG pipelines with self-correcting loops, pgvector search, and Redis streaming—deployed on AWS. My LinkedOut project is a multi-agent system handling 100+ concurrent tasks. Would love to share my GitHub. Available immediately!
GC AI is building an AI platform for in-house legal teams, helping lawyers draft, review, and analyze legal documents. The product is used by 1,800+ companies, including 150+ public companies and 25+ unicorns. GC AI raised a $60M Series B in November 2025 at a $555M valuation.
We’re hiring 5 engineers for the Applied AI team. This is a full-stack product engineering role with a strong AI execution layer — not an ML research or data science position.
We’re looking for engineers with: - Deep, recent TypeScript/JavaScript + React production experience - Hands-on experience shipping LLM-powered product features - Experience with LLM orchestration, RAG, integrations, agents, and/or evaluation systems - Strong end-to-end product ownership, from architecture through production - A track record of shipping quickly and working closely with product
Strong signals include founding/founding-engineer experience, meaningful startup ownership, or experience scaling products at strong engineering companies before moving into a smaller high-ownership environment.
The Applied AI team also owns substantial model evaluation work as new models ship, and builds internal frameworks that allow the team to prototype and productionize new AI capabilities quickly. Location: Remote across the US and Canada Hybrid: Tue–Thu in-office if you’re within ~50 miles of San Mateo, CA or Provo, UT Comp: $180K–$430K + equity Openings: 5 Visa: H-1B transfers supported; no new visa sponsorship
Interested? Email [email protected] with the subject: GC AI – Applied AI Please include: - Your LinkedIn profile - Current location - A short description of an AI/LLM feature you personally shipped to production - GitHub / portfolio if relevant