Founding Engineer

About Camley

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. What Harvey did for legal, we are doing for private markets.

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, incl. 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 + 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 optimise 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

Data-intensive backend work

Early-stage startup experience

Technology stack

Typescript/React, Python (FastAPI), Postgres, AWS, and an agent orchestration layer you will help design.

How to apply

Apply through Wellfound and we will see it. Include your CV with the role title in the subject line. You can include your portfolio, GitHub, and what excites you about the role.

Please do not submit AI generated applications.