Research Engineer (Design) in London

What we're building: Frontier models now score above 170 on IQ tests. Reasoning is no longer the constraint on enterprise AI. Context is. The context layer sits between an enterprise's siloed data and the agents that need to act on it. Stuff the context window and you trade quality for cost and latency. Use naive RAG and retrieval breaks the moment the question gets interesting. Stand up a vanilla knowledge graph and you hit the harder problem underneath: someone has to design the ontology, and at enterprise scale (hundreds of thousands of files, hundreds of gigabytes) no human can.

This is what gates almost every enterprise AI deployment we've seen. 60x solves it. We've built AI Brain, a knowledge graph platform engineered backwards from the agentic retrieval problem. The thesis is dynamic ontology generation: the graph schema isn't authored by a user, it's generated by a multi-agent ingestion pipeline from the business logic of the data itself, and continuously enriched with secondary and tertiary derivatives. Pre-digested analysis lives in the graph so retrieval is a lookup, not a reasoning loop.

We operate a Palantir model for workflows. Platform sits at the centre. Forward-deployed engineers wrap it around enterprise workflows we've already templated. Customisations get retained as IP and feed back into the platform. Same flywheel shape as Palantir, different domain. We work with enterprises across multiple sectors, and a growing list of global consultancies are evaluating us against their internal GPT deployments. In the last two weeks we shipped a redesigned ingestion pipeline, primary entity extraction with auto-enrichment, and an end-to-end demo across 500 companies. That pace is the default.

This is a founding role. The parts of the platform you'll work on are the parts that decide whether the thesis holds.

The role: You'll work on the research-grade core of AI Brain alongside the CTO (exited robotics founder) and the senior engineering team. The open problems on the desk:

• Dynamic ontology generation: The graph schema is generated, not authored. Structure emerges from the business logic of the data, with analytical insight pre-computed and stored rather than recomputed on every query.
• Primary entity consolidation: When a single real-world entity (a company, a person, a product) appears across hundreds of documents under different names, the graph has to recognise it as one thing.
• Our own temporal graph database (Rust): Existing graph stores don't carry the temporal model we need, so we're building our own in Rust.
• Benchmark and white paper: Existing large-context retrieval benchmarks are saturated. We need a new one.
• Frontier work we’ll explore soon: Open ideas from research conversations.

You'll also contribute to hiring, technical input on client engagements where it matters, and white paper authorship.

Our stack: Agents: LangGraph with Pydantic-typed state, Claude via Vertex AI, Gemini for fast tagging. Graph and data: Postgres plus Apache AGE today, with a Rust temporal graph database in active development as the long-term replacement. Backend: FastAPI, Python 3.12, Pydantic everywhere. Frontend: Next.js (App Router), TypeScript, Tailwind, shadcn, Vercel. Infra: GCP across compute, storage, model serving, and key management. Tooling: pnpm, Husky commit hooks (lint, format, typecheck, test, agentic check), Linear, Claude Code as a daily driver.

We're opinionated about code quality and we use AI coding agents hard. Founding-team velocity assumes it.

What we're looking for: Depth in at least one of: knowledge graphs and GraphRAG, retrieval systems, agent orchestration, or large-scale data ingestion. A track record of taking research papers or first-principles thinking through to working production systems. Rust experience. Strong Python, and enough TypeScript to ship product surface where it matters. The instinct to read someone else's PR, see three things to improve, and write the comment kindly. Taste. Excitement about this problem space, not AI in the abstract.

You don't need a PhD. You do need to operate at that level on the problems we care about.

Beyond the role: The community. 60x sits at the centre of Unicorn Mafia, the invite-only builder community we run. Day one, you're in. Events are free. International trips are paid for. We hand-pick who sits in the office to keep talent density high. The lifestyle: We look after the team and we socialise together. Private healthcare and a wider wellness benefits package. Sauna and cold plunge sessions for recovery and team time. Team socials, dinners, off-sites, and the overflow from UM events.