2 of 2 Part-Time Infrastructure Automation Jobs in London

day (Outside IR35) Location: Remote with occasional visits to London (Bishopsgate) Sector: Banking/Financial Services (candidates must pass full bank vetting) Overview Were seeking an experienced VMware vRealize Automation (vRA) Consultant to work within an established financial-services environment, supporting ongoing enhancement, remediation, and automation initiatives. The role combines hands-on development , workflow refactoring , and knowledge transfer … workflow documentation , ensuring solutions are secure, repeatable, and fully aligned with operational standards. Key Responsibilities Provide technical remediation, refactoring, and workflow optimisation within the existing VMware vRA environment. Deliver automation and self-service capabilities for DRaaS failover testing, morning checks, and other Day-2 operational tasks. Collaborate in pair-programming sessions to review and maintain high-quality, efficient code. … maintain onboarding and training materials , supporting upskilling of existing engineering teams. Support and mentor internal staff through knowledge transfer and best-practice guidance. Contribute to continuous improvement initiatives, enhancing automation, reliability, and operational visibility. Essential Skills & Experience Proven experience as a VMware vRA Consultant , DevOps Engineer , or Automation Specialist in enterprise or financial environments. Hands-on expertise with More ❯

AI team thats quickly becoming a key part of their technology strategy. Theyre hiring experienced Software/Platform Engineers to help build and scale their internal AI Platform - the infrastructure, tooling, and developer experience layer that enables teams across the business to develop and deploy AI-driven products. What Youll Be Doing: Designing and building the core AI platform … that supports LLMs, agents, and other AI systems. Developing APIs, SDKs, and orchestration tooling that help product/data teams consume AI capabilities at scale. Automating infrastructure/model deployments using Kubernetes, Terraform, and CI/CD pipelines. Building and managing vector databases and retrieval systems to support RAG pipelines. Working with LLM frameworks like LangChain , LangGraph , CrewAI , or … with Python, Java or Go. Experience with Kubernetes, Terraform, and cloud environments (GCP preferred). Understanding of microservices, distributed systems, and cloud-native architecture. Interest or experience in AI infrastructure, LLM tooling, or AI platform enablement. A collaborative engineer who enjoys problem-solving and contributing to technical direction. If youre interested in helping build real AI infrastructure within More ❯