Founding Engineer

Camley is building the agentic infrastructure for private markets. Our clients are leading private equity and infrastructure investment firms, and we are at the forefront of transforming a $55T asset class that still runs on spreadsheets and software built in the 1990s. We are building the multi-agent architecture that operates funds end-to-end, solving the highest-stakes problems investment firms face with accuracy and speed. Our agents are not just chatbots - they move money and execute workflows autonomously. We are backed by top VCs, including the first investor in Lovable and one of the most technical AI investors in Silicon Valley responsible for building Uber’s core algorithm. Camley is built by a team from Stanford, Harvard, IIT Delhi, and Penn, with decades of industry experience at McKinsey, SquarePoint, and Deutsche Bank, as well as building foundation models for an Accel-backed startup.

About the role: We are hiring a founding full-stack AI engineer. You will build products end-to-end and shape agent architecture and technical decisions alongside the CTO. You’ll build the core intelligence layer - language models for reading documents, a knowledge graph & vector DB for storing data and relationships, a calculation engine for the fund mathematics, and an orchestration layer that coordinates these into workflows that an auditor can sign. You'll own high-impact features across the stack, from model integration to infrastructure. We are a small team working across London and New York. We are open to remote/hybrid for the right candidate. We are a lean team with a high bar for excellence, and hours will at times be intense as in any high-growth startup. In return, you get the autonomy to do some of the best work of your life, and a founding team that values openness, empathy, and not taking ourselves too seriously.

What you will do:

• Design and integrate LLM-powered pipelines and build agents that execute multi-step workflows reliably.
• Build the agent harness: orchestration, tool use, retries, and human-in-the-loop checkpoints, and optimize agent performance across prompts, models, tools, and context.
• Own the evals, validation, audit trails, and observability that keep agent behaviour correct, explainable, and improving.
• Ship features across our React frontend and Python backend, from database schemas and APIs to polished UI, from idea to production.
• Work directly with the founders and early customers to understand real fund workflows, and turn operational pain into shipped product.

What we are looking for: We are looking for an exceptional engineer who wants the autonomy to shape a product from day 0, who loves the challenge of maintaining a strong quality bar while shipping extremely quickly, and who knows how to make smart tradeoffs to get features in front of customers. Strong candidates have:

• Built products from 0 to 1.
• 5+ years of experience building production software.
• Strong full-stack fundamentals across frontend, backend, and infra.
• Proficiency in Python and production experience building LLM systems/agent frameworks.
• High ownership: you do not wait for a spec to start solving a problem.
• Made AI coding tools (Claude Code, Codex, Cursor, or similar) a core part of how they work.
• Passion for building effective domain-specific agents.

Bonus points if you have:

• Experience in finance or financial services.
• Early-stage startup experience.
• Typescript/React, Python (FastAPI), Postgres, AWS, and an agent orchestration layer you will help design.