Senior Software Engineer

Radiant; Greater London; Hybrid; GBP 100,000 - 160,000; Full time

Benefits offered by this job

25 days annual leave

Private medical insurance (Bupa)

Cycle to Work Scheme

Gympass subscription

Company shares program

Enhanced parental pay & leave

Learning Time

Job summary

Radiant is hiring a Senior Software Engineer to own major parts of its AI cloud platform. You will join one of five teams—Infra, Cluster, Observability, MLOps Training, or MLOps Inference—and be matched to the best fit for your experience.

You will design, build, and operate distributed services at datacentre scale, collaborating with product, infrastructure, SRE, and other engineers. You’ll translate product requirements into robust designs and APIs, improve testing and performance, and

Qualifications

• Solid hands-on engineering skills in Go or similar.
• Depth in infrastructure, cluster management, observability, or MLOps (training or inference).
• Comfortable working in Linux and with Kubernetes and containers.
• Clear communicator who takes ownership of their work.

Responsibilities

• Design, build, and operate distributed services for your team's part of the platform.
• Own features from design through production, operation, and continuous improvement.
• Translate product requirements into clear technical designs and APIs.
• Improve testing, reliability, and performance across your services.
• Take part in on-call and incident response for the systems you build.
• Mentor engineers and contribute to design and code review.

Skills

Go

Distributed systems

Linux

Kubernetes

Tools

Container runtimes

Job description

What You'll Do

As a Senior Software Engineer, you will own major parts of the company's AI cloud platform, joining one of five teams: Infra, Cluster, Observability, MLOps Training, or MLOps Inference. We'll match you to the team that fits your experience.

You'll design, build, and run distributed services at datacentre scale, working closely with product, infrastructure, SRE, and the other engineering teams.

The teams

• Infra: the core infrastructure our AI cloud runs on, from datacentre to platform
• Cluster: provisioning and operating the GPU clusters customers run their workloads on
• Observability: FlightDeck, the platform customers and operators use to observe and operate AI infrastructure
• MLOps Training: the platform customers use to run large-scale model training
• MLOps Inference: the platform customers use to serve models in production

Key Responsibilities

Design, build, and operate distributed services for your team's part of the platform.

• Own features from design through production, operation, and continuous improvement.
• Translate product requirements into clear technical designs and APIs.
• Improve testing, reliability, and performance across your services.
• Take part in on-call and incident response for the systems you build.
• Mentor engineers and contribute to design and code review.

Your Profile

Solid experience building and running production software, ideally distributed systems.

• Strong hands‑on engineering skills in Go or similar.
• Depth in at least one of: infrastructure, cluster management, observability, or MLOps (training or inference).
• Comfortable working in Linux and with Kubernetes and containers.
• Clear communicator who takes ownership of their work.

What You Bring

Domain depth: Bring real expertise in your team's area, and keep building it.

• Engineering quality: Write clean, tested, maintainable code, and review others' work with care.
• Ownership: Take features from design through production, and stay accountable for how they run.
• Pragmatism: Ship what matters, simply, and improve it from real‑world feedback.
• Collaboration: Work openly with product, infrastructure, SRE and customers, and share what you learn.

Qualities we look for:

Set the standard: Every single day, you spot opportunities to constructively shake things up

• Inspire the change: There's no blueprint for the future. You'll embrace challenges and change
• You're real and you're true to yourself: We cherish and celebrate diversity so you'll feel right at home whoever you are and whoever you're talking to, you treat everyone the same.

Why should you join us?

What sets us apart is our blend of modern technology, competitive benefits, and an open, welcoming work culture that enables our people to thrive.

Here are just some of the great things you can expect from us:

• 25 days of annual leave
• A culture that emphasises results over hierarchy, process & ego: we place great emphasis on the quality, ingenuity and creativity of work.
• Open communication, regular feedback: we value smooth collaboration, direct and actionable feedback, and believe that leading with empathy and a growth mindset makes us better together.
• Learning Time: we all have dedicated learning time to focus on new skills, projects or interests that lay outside of your day‑to‑day job.
• Health & Wellbeing: we want everyone to feel healthy and happy, so we offer private medical insurance via Bupa.
• Cycle to Work Scheme: we're committed to building a sustainable business, so we encourage cycling to work.
• Gympass subscription to a variety of gyms and wellbeing apps
• Participation in the company shares program
• Enhanced parental pay & leave

Our process: Talent screen → Hiring Manager → Technical interview (two engineers) → Final.

Company Overview:

the company is redefining how AI infrastructure is built.

We design and operate AI‑native cloud platforms engineered for sovereignty, performance, and scale. Our infrastructure powers GPU‑native workloads, multi‑tenant control planes, and high‑performance AI systems designed for the most demanding environments.

We are not building a generic cloud. We are building purpose‑built AI infrastructure — from powered land, to compute, to software.

As we scale, we're building this organisation from the ground up. We're looking for people who'd rather build the playbook than inherit one — who are comfortable doing the work themselves as well as directing others, and who can adapt as fast as our strategy does. This is a startup model: attitude and adaptability matter more to us than years of experience or the size of the team you've previously managed.

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