Platform Engineer

About Freetrade

Freetrade’s mission is to become the default place to invest. Investing has been too complicated and expensive for too long, keeping millions from making the most of their savings.

We’re changing that.

We’re building our team and looking for people who are excited to reshape how our customers invest and grow their wealth. If you’re driven by solving complex problems and building innovative products, you’ll fit right in.

2026 is a big year for us. Last year, we announced a game changing deal to become part of the IG Group. We’ll continue to operate as an independent business while gaining access to the resources and support of an established leader in the space.

This year, we’re accelerating our roadmap and taking our products to the next level. We’re building new features like mutual funds, bonds, and family investment tools. We’re also exploring how we can leverage AI to deliver an even better experience for our customers.

Freetrade exists to get everyone investing. Underneath that is a platform moving real people's money, and a small team building the foundational parts every engineer relies on to ship: the CI/CD pipelines that carry every deploy, the logging and observability that make production legible, the infrastructure and architecture our systems run on, and the security that keeps it all worthy of our customers' trust. We treat that platform as a product; our customers are Freetrade's engineers. We're looking for a Platform Engineer to help us build it. The team

As part of the Platform Engineering Team, you'll work across a wide surface area at Freetrade: product engineering, frontend, security product, design, risk & compliance and data. You'll see more of Freetrade's engineering than almost anyone else here, and you'll have experienced engineers around you to learn from.

What you'll be doing

Contribute to our Google Cloud infrastructure; Kubernetes, serverless, and Terraform; working with engineering teams to build paved paths that make the right infrastructure choice the easy one.

Improve the path from commit to production: faster builds, safer rollouts, clearer failures across our CI/CD infrastructure.

Treat the platform as a product: look ahead at Freetrade's product roadmap, anticipate what engineering teams will need from the platform to deliver it, and partner with those teams to design and scale services that meet the business's needs

Work with teams to build AI into their engineering workflows; development, debugging, incident investigation; evaluating honestly where it works and where it doesn't, and evolving our tooling, context, and guardrails as the AI landscape changes.

Support our monitoring and diagnostics, working with engineering teams towards best-in-class observability, alerting, and SLOs; so teams can operate their own services

Partner with our security, risk, and compliance teams to ensure our infrastructure meets the regulatory bar for a financial services company; turning requirements into guardrails so engineers ship compliantly by default.

Deploy, monitor, and maintain what you build in production, growing into ownership of whole platform areas as you build context.

About you

You've built, shipped, and run production backend services; you know the whole journey from code review through deployment to living with what you shipped, not just the coding part.

Platform interests and curiosity; you don’t need hands-on experience managing platforms, but you've built backend services in any industry (finance experience isn't required), and want to understand the platform underneath them: how things ship, run, and scale.

Languages and tools: we don't hire for a specific language; bring whatever you're strongest in, as long as you can show you understand what's happening beneath it: how your code actually runs, where it spends its time, and what it does to the systems around it. Day to day we work with Node.js (TypeScript), Terraform, and Kubernetes, and we'll support you getting up to speed.

You've worked hands-on with a major cloud provider (GCP is a bonus, AWS or Azure transfer fine), used Infrastructure as Code like Terraform (even if someone else set it up), and deployed to Kubernetes, serverless, or both.

You've gone beyond using CI/CD pipelines: you've fixed a broken build, sped one up, or become your team's unofficial pipeline person.

You think like a product engineer: you want to know where the product is going and why, you've changed what you built because of how people actually used it, and you'd measure success in this job by other engineers shipping faster and safer.

You use AI tools critically in your daily work and can speak concretely about where they fail and why, judgment matters here, not ML expertise.