AI Research Engineer (Staff)

An opportunity to build the environments that let AI agents learn from doing, not just from data.A young, extremely well-backed AI company whose work feeds directly into the top research labs.Real technical ownership at the most senior IC levels - with your hands still on the work.The frontier is shifting from training on fixed data to learning through experience. Our client builds the software worlds where AI agents practise real tasks - from simple web apps through to full enterprise systems - stumble, and get sharper with every attempt, producing the hands-on training signal that enhances models further. That work goes straight into the research pipelines of the top labs. They're now adding senior Research Engineers who can set direction across the hardest AI problems while staying deep in the work - people who lead through judgement, not job title.What You'll Be DoingTake a major AI or research-engineering area and carry it the whole way - from framing the problem and choosing the direction to something that moves in productionBreak vague, company-sized questions down into concrete experiments, priorities, and a clear way to tell whether they're workingDrive how training data gets made and curated, how models are fine-tuned and post-trained, and how agents are measured and improvedBuild and refine the harnesses, sandboxed execution and feedback loops that let agents run, get scored, and improve inside interactive workflowsDecide where the leverage is: which experiments to run, what "good" looks like, and when to double down, scale, or walk away from an approachGet promising prototypes out of research and into dependable, well-instrumented production, working shoulder to shoulder with the software engineersSteer big, multi-person efforts through the strength of your calls rather than a reporting line - lifting the quality of everyone else's technical decisions while keeping your own hands in the codeWhat You'll NeedEssentialYou've trained, fine-tuned or post-trained models yourself, and you know how to tell whether what you did actually moved the needleA real command of modern ML - post-training, reinforcement learning, optimisation and evaluation - not just passing familiarityGenuine software-engineering depth: you write, review and defend production code, not just prototypesA history of taking messy, ill-defined problems and turning them into something that shipsYou've run significant technical efforts over months, carrying several people with you without formal authority over themLow ego, and a deliberate choice to stay an individual contributor rather than manageBonusYou've built serious agents, agent harnesses, evaluation stacks or sandboxed execution infrastructureYou've owned training-data or synthetic-data pipelines at real scaleSomething you trained or fine-tuned set the bar in a domain that matteredYou've managed people before and chose to come back to a hands-on senior trackA strong research or academic grounding - a plusThe PersonYou want the authority to shape hard technical direction without being pulled away from building it. You're at home when the goal is clear but the route isn't, happy to commit on partial information and change your mind quickly when the data says so. You move easily between reasoning from first principles and just shipping the pragmatic thing, and you'd rather make the engineers around you sharper than outrank them.The RoleAround two days a week in the officeHired at Staff or Principal, with the level set by the ownership and judgement you show through the processStrongly competitive salary and meaningful equityHands-on at every level - you stay in the code, the experiments and the calls