Staff Engineer - Platform & Tooling

AtomInvest Ltd.; Greater London; Presencial; GBP 110.000 - 150.000; Jornada completa

Descripción de la vacante

Atominvest in the United Kingdom is seeking a seasoned engineer to own the platform our clients run on and to build the AI development harness used by our engineers daily.

The role spans infrastructure to application code, demanding breadth across systems and depth in at least one area, with a focus on reliability, security and scalable design.

Responsabilidades

• Own the platform our clients run on and build the AI development harness our engineers work in day to day.
• Work across infrastructure to application code, bringing breadth and depth in at least one area.
• Design for reliability, security, audit-readiness and scalable growth as deployments expand.

Descripción del empleo

Who is Atominvest

Atominvest is the operating system for modern private markets asset managers. Our modular, flexible SaaS technology underpins key investor- and portfolio-management workflows.

Our customers are sophisticated private equity, growth equity, and private credit firms managing billions in assets globally. We aim to deliver ongoing high-quality outcomes for them through a long-term partnership mindset.

At Atominvest, you’ll be working on something very exciting: the future of work, investments and sustainability/ ethical investing for the world’s best investors and delivering a positive impact through this. Based on the growth we are experiencing, we think we’re on to something big.

It won’t be easy. Joining a scale up business is an amazing and rewarding challenge, pushing well beyond the boundaries of natural growth cycles. You’ll move quicker than feels comfortable and be brilliant at continually re-prioritizing what must get done to keep Atominvest growing year over year at the pace of the best SaaS companies on the planet.

We’ve gone from zero to ten, now we’re looking to go from ten to one hundred!

About the role

Hi, I'm Thomas, VP Engineering at Atominvest. This is the hire I'm most excited about, so I wanted to tell you about it myself.

You'll own the platform our clients run on and build the AI development harness our engineers work in day to day. That work runs from infrastructure to application code, so we're looking for an experienced engineer with breadth across both, and depth in at least one. Together, it's what lets a small, lean team, working alongside AI agents, ship like a much bigger one.

By platform, we mean everything our product and our engineers stand on: infrastructure, security, test automation, developer experience, and the agent pipelines that run through all of them. It's a broad, hands‑on role. You'll write infrastructure as code for a new service one day and address network vulnerabilities the next, then enhance our AI development harness and release a new feature, all within the same month.

You might be a platform engineer who loves shipping product, or a full-stack engineer who has run serious production infrastructure. Either works.

As deployments grow more complex, the team needs your depth in infrastructure and distributed systems. You'll strengthen the architecture and make the design decisions the platform will rest on for years. Those decisions should leave room to grow, because future products may bring much larger volumes of data than we handle today.

It has to stay dependable while we do it. Our software needs to be available around the clock, every day of the year, and data integrity is critical. Our clients use Atominvest to report to their own investors, so a wrong number matters as much as an outage. Security, reliability and audit‑readiness matter too. If you enjoy getting those right without slowing everything else down, you'll find plenty of fun things to work on.

The machine that builds the product

We're becoming AI-native. Agents do more and more of the mechanical work of writing code, and engineers build the machine that builds the product: the architecture, the specs, the limits agents work within, and the evals that tell us whether their output is right.

I think that moves an engineer's leverage upstream. When code is cheap, the scarce things are judgement and understanding. Which problem is worth solving? What does good look like for the person using it? Is the output actually right? Did what we shipped help? The best engineers I've worked with always solved the end problem, with code as the medium. Now that's most of the job.

That's why product and user understanding sit at the centre of how we work. An engineer who knows our clients’ workflows can point agents at the right problem and spot when the result is subtly wrong. Without that, agents just build the wrong thing faster.

Your part is the AI development harness that makes this safe. That means sandboxed environments with synthetic data, scoped and audited access to logs and alerts, and evals and validation gates in CI. It also means firm lines, enforced by tooling, that keep production deploys