7 of 7 Deployment Automation Jobs in Central London

support the full lifecycle of modern cloud-hosted applications. Role Overview You will be responsible for building and managing Azure cloud environments, automating deployment pipelines, enhancing reliability through SRE practices, and ensuring compliance with security and governance standards. This is an excellent opportunity for an experienced cloud engineer … thrives in a collaborative, fast-moving environment and is passionate about automation, optimisation and best practice engineering. Key Responsibilities Cloud Infrastructure Design & Build Design, implement and maintain scalable Azure cloud infrastructure using Terraform and IaC principles. Deployment Automation & CI/CD Build and maintain CI/ ...

Proven track record building integrations via Azure Integration Services, REST/SOAP APIs, custom connectors Azure DevOps Experience with CI/CD pipelines, solution deployment automation, and branching strategies Architecture Ability to design scalable enterprise solutions aligned to Microsoft Well-Architected Framework Agile Strong working knowledge of Agile ...

independently and communicate risk and findings clearly to senior traders and management Cloud infrastructure - Azure preferred, AWS considered; IAM, managed services, automated and auditable deployment pipelines, secrets management Nice to Have Market making, systematic execution, or electronic trading in energy or commodity derivatives Asian options, barrier structures, or path ...

Code (IaC), Policy-as-Code and automated security validation Design and implement security configuration baselines across the PDS cloud estate Develop and maintain automated deployment scripts and policy frameworks to ensure consistent configuration and compliance across cloud environments Implement policy-as-code approaches using policy tools, scripting (PowerShell, Bash … services across cloud platforms Develop DevSecOps tooling and scripts to allow engineering teams to deploy secure configurations consistently Produce reusable security modules, scripts and automation pipelines to embed security controls into platform builds Support implementation of continuous compliance and automated security validation within CI/CD pipelines Demonstrate ...

/OpenTofu, and modern CI/CD pipelines, while helping define best practices for a regulated, high-impact platform. What You’ll Do: Infrastructure & Automation: Build and maintain cloud infrastructure, CI/CD pipelines, and automated deployment workflows. Security & Compliance: Implement automated security controls and policies across cloud … . Hands-on experience with security tooling (Aqua, Falco, Prisma Cloud, or similar). Programming or scripting experience in Python, Golang, or Shell for automation tasks. Strong understanding of API security, IAM policies, network security, and secrets management. Bonus Points For: Experience in regulated fintech or compliance frameworks (SOC2 ...

management, routing/navigation, error handling, data fetching and modularization strategy. Design, publish and own engineering standards including coding standards, CI/CD strategy, deployment blueprint, testing automation strategy, observability design and security baseline. Tackle high-impact problems: performance bottlenecks, reliability issues, scaling limits, complex integration, tech debt …/integration experience: REST/GraphQL, auth flows, contract design and resilience patterns Well versed in latest CI/CD practises and tools, deployment methodologies and experienced in tools to enforce quality standards. Expertise in complex state management and understanding the nuances between DOM based and Native based styling ...

build and deploy production computer vision and agentic AI systems powering search, recommendations and personalisation Own the full data science lifecycle: problem framing → modelling → deployment → monitoring → iteration Make pragmatic trade-offs between speed, quality and technical elegance Product & User Impact Translate messy real-world user problems into testable … imperfect datasets Design annotation strategies, data quality frameworks and evaluation pipelines Decide where data investment matters most Technical Direction & MLOps Establish pragmatic MLOps practices (deployment, monitoring, iteration) Build scalable but lightweight ML pipelines in AWS alongside engineering Ensure models are robust, reliable and safe for production Team & Culture ...