Job Title
Platform Engineer
Salary
Not Disclosed + Equity
Company Description
Model ML is a $75M Series A London fintech building an AI workflow platform for global financial institutions, backed by FT Partners, Y Combinator, and LocalGlobe.
Job Description
As a Platform Engineer at Model ML, you will architect and scale the cloud infrastructure powering a leading enterprise AI platform. You'll own the transition to automated AI systems for major financial institutions, driving operational excellence through Kubernetes, Terraform, and Azure while ensuring the highest standards of security and compliance readiness.
Location
London, UK
Why this role is remarkable
- Join one of the fastest-growing enterprise AI platforms globally, having recently closed a $75M Series A—one of the largest fintech rounds ever.
- Report directly to founders with two successful venture‑backed exits, gaining a front‑row seat to building a generational AI company from the ground up.
- Take complete ownership of a high‑load, production‑grade infrastructure, scaling systems ahead of demand for some of the world's largest financial institutions.
What You Will Do
- Architect and maintain cloud infrastructure using Azure (AKS), Terraform, and Docker to support rapid product growth and global scaling.
- Build and optimize robust CI/CD pipelines for backend, frontend, and data services using GitHub Actions to enable high‑velocity, reliable releases.
- Drive product‑wide observability systems for logging, metrics, and tracing, while preparing infrastructure for SOC 2 and ISO 27001 audit readiness.
The ideal candidate
- Has 4-7 years of platform or DevOps experience, ideally within a high‑growth startup environment or handling high‑load production systems.
- Possesses deep technical expertise in Azure, Terraform, Kubernetes (AKS), and scripting languages like Python or Bash for automation.
- Demonstrates a proven track record of owning infrastructure end‑to‑end, including networking, database management (PostgreSQL), and implementing security best practices.
