Lead Platform Engineer

Lorien; England; On-site; GBP 110,000 - 150,000; Full time

Job summary

Lorien seeks a Lead Platform Engineer to design, build and operate an MLOps platform on Kubernetes. This senior, hands-on technical leadership role focuses on deploying scalable ML and LLM workloads while working closely with data scientists and ML engineers.

You’ll own operability, reliability, security, and production support, ensuring a usable, well-documented platform that meets real production needs.

Qualifications

• Senior or Lead Platform Engineer with hands-on DevOps experience.
• Experience building Kubernetes-based platforms.
• Proficiency with Helm and Infrastructure as Code (Terraform).
• Experience extending Kubernetes with higher-level platforms and services.
• Strong ops fundamentals: monitoring, logging, incident response, reliability.
• Ability to work with data scientists to support production workloads.

Responsibilities

• Provide technical leadership across platform, DevOps, and MLOps.
• Design, build, and operate a Kubernetes-based MLOps platform.
• Implement and run MLOps tooling enabling experiments, packaging, deployment, and scalable inference.
• Build and operate model serving and inference platforms within Kubernetes.
• Work with data scientists and ML engineers to ensure usability and proper documentation.
• Own platform operability, reliability, security, and support in production.
• Troubleshoot complex issues across Kubernetes, platform services, and MLOps layers.
• Contribute to architectural decisions while remaining hands-on with delivery.
• Apply pragmatic engineering judgement in AI workloads.

Skills

Kubernetes

MLOps

DevOps

Helm

Terraform

Platform engineering

Leadership

Data scientist collaboration

Tools

Kubeflow

KServe

vLLM

JupyterHub

Kubernetes extensions

Terraform

Helm

Job description

Lead Platform Engineer - Must be DV Clearable - 5 days a week on-site

Building the platforms that make AI and machine learning work in production

We're looking for a Lead Platform Engineer to join a growing engineering organisation and play a pivotal role in designing, building, and operating an MLOps platform that enables AI and data science teams to deliver reliably in production.

This is a senior, hands‑on technical leadership role, not a people‑management position. You'll lead through technical depth, judgement, and delivery, building the tooling, workflows, and operational foundations that allow data scientists and ML engineers to experiment, deploy, and run ML and LLM‑based workloads safely and at scale.

The focus is not simply on running Kubernetes clusters - it's on layering real MLOps capability on top of Kubernetes to create a platform that is usable, supportable, and trusted in live environments.

What you'll be doing

You'll act as a technical leader across platform engineering, DevOps, and MLOps, remaining deeply involved in implementation.

You will:

• Provide technical leadership across platform, DevOps, and MLOps activities
• Design, build, and operate a Kubernetes‑based MLOps platform supporting the full model lifecycle
• ImplementandrunMLOps tooling that enables teams to:Experiment with models and notebooksPackage, version, and deploy modelsRun scalable inference and LLM‑based workloads
• Build and operate model serving and inference platforms within Kubernetes environments
• Work closely with data scientists and ML engineers to ensure the platform is usable, well‑documented, and aligned to real workflows
• Own platform operability, reliability, security, and supportability in production
• Troubleshoot complex issues across Kubernetes, platform services, and MLOps layers
• Contribute to architectural decisions while staying hands‑on with delivery
• Apply pragmatic engineering judgement in environments where AI workloads place real operational demands on infrastructure

What we're looking for

This role suits someone who is fundamentally a strong platform engineer, with the depth to apply those skills confidently to MLOps.

• Strong background as a Senior or Lead Platform Engineer / DevOps Engineer
• Deep, hands‑on experience building and operating Kubernetes‑based platforms
• Strong practical experience with Helm and Infrastructure as Code (. Terraform)
• Proven experience extending Kubernetes with higher‑level platforms and services, not treating it as the finished product
• Strong understanding of operational fundamentals: monitoring, logging, incident response, reliability, and maintenance
• Comfortable working directly with engineers and data scientists to support real production workloads

MLOps experience (key to the role)

You'll work deeply "in the weeds" of MLOps platforms, enabling ML and LLM workloads (not model research).

Experience in areas such as:

• Building or operating MLOps platforms using tools like Kubeflow or similar frameworks
• Running model serving and inference platforms (. KServe, vLLM, or equivalent)
• Supporting LLM‑based workloads, including optimisation and serving considerations
• Providing notebook‑based environments such as JupyterHub in secure platforms
• Exposure to emerging tooling such as InstructLab, Trustworthy / Responsible AI tooling, or comparable solutions
• Building internal platforms specifically for data science and ML teams
• Experience in regulated, security‑conscious, or high‑assurance environments
• Designing platforms that balance user flexibility with governance and control