Cloud DevOps Engineer (Performance) in London

Energy Jobline ZR; City Of London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A global energy job board is seeking a Senior DevOps Engineer with expertise in AI technologies and public cloud environments. This hybrid role involves designing and managing cloud infrastructure, optimizing CI/CD pipelines, and containerizing workloads. The ideal candidate will have a strong background in DevOps, experience with MLOps practices, and proficiency in Python scripting. Join us in shaping the future of AI-driven public services.

Qualifications

• Experienced as a DevOps or Cloud Engineer in public cloud environments.
• Skilled in deploying AI/ML workloads using MLOps or LLMOps practices.
• Proficient in scripting and automation using Python.

Responsibilities

• Design and provision secure cloud infrastructure using Terraform or Pulumi.
• Build and optimise CI/CD pipelines for AI applications.
• Containerise workloads with Docker and manage with Kubernetes.

Skills

DevOps or Cloud Engineering in public cloud environments

Infrastructure for AI/ML workloads using MLOps or LLMOps

Scripting and automation skills in Python

Python-based IaC frameworks

CI/CD pipelines for AI deployments

Containerisation and orchestration tools

Tools

AWS

Azure

GCP

Docker

Kubernetes

Job description

Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide.

We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.

Job Description

Senior DevOps Engineer (MLOps / LLMOps)
Clearance: Eligible for BPSS
Start: ASAP
Work pattern: Hybrid (London)
Work type: 12 month FTC (Competitive Salary)

We’re working with a major UK government initiative that’s shaping the future of how we interact with public services. The programme focuses on harnessing the latest AI technologies to deliver simpler, faster, and more efficient digital experiences across departments.

We’re looking for an experienced Cloud & DevOps Engineer to join the AI Customer Experience team - a multidisciplinary group driving innovation in Generative AI, conversational interfaces, and automation.

You’ll design, build, and manage the infrastructure that powers large‑scale AI services and agentic workflows across government systems.

Key Responsibilities

• Design and provision secure, scalable cloud infrastructure (AWS, Azure, or GCP) using Python-based Infrastructure as Code (Terraform or Pulumi).
• Build and optimise CI/CD pipelines to automate the deployment of AI applications and models (MLOps / LLMOps).
• Containerise workloads using Docker and manage deployments through Kubernetes (KubeRay, Kubeflow, MLRun, or similar).
• Provision and manage the infrastructure required to run AI workloads, including vector databases and hyperscaler AI services.
• Develop automation scripts in Python to streamline operations and reduce manual tasks.
• Implement comprehensive monitoring, logging, and alerting to maintain high system reliability and performance.
• Provide technical support for complex issues and advise on modern engineering practices for large‑scale projects.

Skills & Experience

• Strong background as a DevOps or Cloud Engineer in public cloud environments (AWS, Azure, or GCP).
• Experience deploying and managing infrastructure for AI/ML workloads using MLOps or LLMOps practices.
• Excellent scripting and automation skills in Python (e.g. Boto3, SDKs).
• Proven experience with Python-based IaC frameworks (Pulumi, Terraform, CDKs).
• Hands‑on experience building CI/CD pipelines for AI deployments (Github Actions, MLFlow, ZenML, or similar).
• Deep understanding of containerisation and orchestration tools (Docker, Kubernetes).

Desirable

• Experience deploying AI inference engines (vLLM, Ray Serve, Triton).
• Familiarity with observability tools for LLMs (TruLens, Helicone, LangSmith).
• Understanding of AI safety and reliability frameworks (Guardrails AI).

This is an exciting opportunity to help define the infrastructure powering the next generation of AI‑driven public services. If you have the experience and passion to work on impactful projects within government, we’d love to hear from you.

To apply, press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.