DevOps Engineer (+ Equity) at Fast-growing AI infrastructure startup

Jack & Jill/External ATS; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A fast-growing AI infrastructure startup in London is seeking a DevOps Engineer to build and scale an RLOps platform. The role involves designing cloud infrastructure, optimizing CI/CD pipelines, and implementing containerization strategies. Ideal candidates should have experience with major cloud platforms and strong skills in Kubernetes and Terraform. Enjoy autonomy, flexible working options, and significant equity as part of a funded startup focused on innovation in AI.

Benefits

Significant equity

Flexible working policies

Dedicated annual learning budget

Qualifications

• Professional experience managing compute-intensive workloads.
• Strong proficiency in Kubernetes and Terraform.
• Solid scripting skills in Python or Bash.

Responsibilities

• Design and maintain scalable cloud infrastructure on AWS, GCP, or Azure.
• Build and optimize CI/CD pipelines using GitHub Actions or GitLab CI.
• Implement containerization and orchestration strategies using Docker and Kubernetes.

Skills

Managing compute-intensive workloads

Container orchestration (Kubernetes)

Infrastructure as Code (Terraform)

Scripting in Python or Bash

MLOps practices

Monitoring tools

Secure networking for distributed systems

Tools

AWS

GCP

Azure

Docker

GitHub Actions

GitLab CI

Job description

DevOps Engineer

Company Description: Fast-growing AI infrastructure startup

Job Description: As a DevOps Engineer, you will build and scale a first‑of‑its‑kind RLOps platform. You will design robust cloud infrastructure and CI/CD pipelines to support high-performance reinforcement learning workloads. This role is pivotal in enabling businesses to deploy sophisticated AI models at scale using state‑of‑the‑art open-source frameworks and enterprise tools.

Location: London, UK

Why this role is remarkable:

• Work at the absolute forefront of reinforcement learning innovation, building the infrastructure that powers next‑generation AI reasoning and autonomous systems.

• Join a well‑funded startup backed by top‑tier investors, offering significant equity and the chance to shape a culture of excellence and collaboration.

• Enjoy high autonomy with flexible working policies, including a 6‑month remote option and a dedicated annual learning budget for professional growth.

What you will do:

• Design and maintain scalable cloud infrastructure on AWS, GCP, or Azure to support distributed machine learning training environments and GPU clusters.

• Build and optimize CI/CD pipelines using GitHub Actions or GitLab CI to automate testing and deployment for both open-source and enterprise platforms.

• Implement containerization and orchestration strategies using Docker and Kubernetes, alongside Infrastructure as Code solutions like Terraform to ensure reproducible environments.

The ideal candidate:

• Professional experience managing compute‑intensive workloads and ML/AI services within major cloud platforms like AWS, GCP, or Azure.

• Strong proficiency in container orchestration (Kubernetes) and Infrastructure as Code (Terraform) to manage high-performance computing resources.

• Solid scripting skills in Python or Bash with a deep understanding of MLOps practices, monitoring tools, and secure networking for distributed systems.

Next steps:

Step 1. Visit our website.
Step 2. Click 'Talk to Jack'.
Step 3. Talk to Jack so he can understand your experience and ambitions.
Step 4. Jack will make sure Jill considers you for this role.
Step 5. If Jill thinks you're a great fit and her client wants to meet you, they will make the introduction.
Step 6. If not, Jack will find you excellent alternatives. All for free.