Site Reliability Engineer (SRE)/Platform Engineer

Key Responsibilities

• Design, build, and maintain cloud infrastructure within Google Cloud Platform (GCP).
• Deploy, manage, and optimise Kubernetes-based environments and containerised applications.
• Develop and support Back End services and operational tooling using Python.
• Create and maintain Infrastructure as Code using Terraform.
• Implement security hardening, monitoring, observability, and reliability best practices across cloud platforms.
• Troubleshoot and resolve complex production issues, ensuring minimal service disruption.
• Develop and improve CI/CD pipelines to enable efficient and reliable software delivery.
• Work closely with development teams to improve platform resilience, scalability, and operational performance.
• Implement monitoring, alerting, and incident response processes to support production systems.
• Drive automation initiatives to reduce operational overhead and improve system reliability.

We're Looking For

• Proven experience as a Site Reliability Engineer, Platform Engineer, Cloud Engineer, or DevOps Engineer.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Experience deploying, operating, and supporting production cloud applications at scale.
• Strong knowledge of Kubernetes and container orchestration technologies.
• Commercial experience developing with Python.
• Experience building and supporting Back End services and APIs, ideally using FastAPI.
• Strong knowledge of Terraform and Infrastructure as Code principles.
• Experience designing highly available, resilient, and secure cloud environments.
• Strong troubleshooting and incident management skills within production environments.
• Experience with CI/CD pipelines, Git, GitHub, and DevOps best practices.
• Strong understanding of cloud networking concepts, with particular emphasis on GCP networking.
• Ability to take ownership of production systems and drive continuous improvement initiatives.

Desirable

• Microsoft Azure experience.
• Experience deploying and supporting AI/ML applications in production environments.
• Exposure to Large Language Models (LLMs), NLP, or agent-based systems.
• Experience with observability and monitoring tools such as Sentry, Prometheus, Grafana, or similar platforms.
• Strong Docker and multi-container application architecture experience.
• Experience working within scientific, pharmaceutical, genomics, or bioinformatics environments.
• Start-up or high-growth technology company experience.
• Open-source software contributions.
• Technical leadership, mentoring, or coaching experience.

Contract Details

• 6-Month Initial Contract
• Inside IR35
• London-based
• Hybrid Working (2 days onsite per week)
• Competitive Day Rate
• Potential extension opportunities

The Opportunity

This role offers the chance to work on modern cloud-native systems supporting innovative AI-enabled technologies.

You'll be part of a collaborative engineering environment where reliability, automation, security, and scalability are key priorities, with the opportunity to make a significant impact on critical production platforms.