17 of 17 Deployment Automation Jobs in Central London

processing solutions. Design and implement PySpark data pipelines using Microsoft Fabric. Establish and maintain CI/CD pipelines using GitLab to support automated deployment and delivery. Develop and maintain unit and integration tests using Pytest and associated testing frameworks. Collaborate with architects, developers, and DevOps teams to integrate Cosmos ...

with PostgreSQL, Redis, MongoDB, or similar. Messaging Systems Experience with Kafka, RabbitMQ, or event-streaming platforms. CI/CD Strong understanding of automated testing, deployment pipelines, and observability. Leadership Proven ability to lead teams, influence stakeholders, and deliver complex projects. FinTech Domain Knowledge Experience in payments, trading, banking ...

platform engineering capability, with the role expected to evolve as they scale. This is a platform enablement role, not traditional ops support - focused on automation, operational maturity, resilience, and developer experience. Key Responsibilities Design, build, and maintain scalable cloud infrastructure and platform tooling Improve reliability, observability, deployment automation … systems, event-driven architecture, or streaming platforms Working knowledge of RBAC, IAM, secrets management, and operational security practices, ideally in a regulated environment Strong automation/scripting ability and systems-thinking approach Comfortable operating in a scaling, growth-stage environment Key Competencies Automation-first, ownership-driven mindset Strong ...

grade use of AI coding assistants - Claude Code, GitHub Copilot, or equivalent agentic tooling - to build and ship real software, not just autocomplete. Building automation and tooling that operates on real codebases: code parsing/transformation, templating, and generating change as reviewable pull requests. Cloud-native platforms and their … primitives: Kubernetes, containers (Docker/OCI), and at least one of AWS, GCP, or Cloud Foundry/VCF. CI/CD and automated deployment pipelines. Designing validation and guardrails for automated change, testing, verification, and safe rollback. End-to-end application infrastructure concerns such as authentication/authorization ...

like Java, Python, Go, or Rust . Cloud & DevOps: Solid understanding of modern cloud platforms ( AWS, Azure, or GCP ) and automated CI/CD deployment pipelines. Industry Frameworks: Prior experience working within heavily regulated environments (FinTech, Banking, or Enterprise) with an understanding of cryptography and data sovereignty. ...

Google Inc. in the United Kingdom seeks a Network Implementation Engineer to lead deployment, maintenance, and operations of private data networks worldwide. You will work with Technical Program Managers, Network Engineers, Design and Infrastructure Engineers, Field Engineers within Google, as well as contractors and vendors to position the team ...

resolution of cross-program blockers AI & Digital Transformation Leadership Lead end-to-end delivery of AI-powered transformation programs including GenAI, ML model deployment, intelligent automation, and advanced analytics platforms Partner with AI Architects, Data Scientists, and Product teams to translate AI strategy into delivery roadmaps and executable … plans Oversee deployment of AI use cases across Clinical Trial Operations, Drug Discovery, Regulatory Affairs, Pharmacovigilance, and R&D pipelines Champion a culture of innovation, experimentation, and responsible AI within delivery teams Stakeholder & Executive Engagement Act as the primary point of contact for C-suite and senior stakeholder communities ...

disciplinary and multi‐cloud environments. Develop accelerators, reference architectures, and reusable assets for agentic AI patterns. Guide engineering, data, and DevOps teams on AI automation and pipeline integration. Travel occasionally for high‐value client engagements. Skills and Experience 12+ years of experience designing and developing enterprise‐scale applications. Strong … integrating AI into distributed systems, microservices, APIs, and event‐driven architectures. DevOps and MLOps experience including CI/CD, IaC, automated testing, observability, and deployment automation. Familiarity with data engineering, ML models, Responsible AI, and enterprise governance. Ability to communicate complex AI concepts to both technical and executive audiences. ...

Responsibilities: Develop and implement Salesforce Service Cloud solutions based on provided designs. Customize and configure Service Cloud features, including case management, knowledge base, automation, and workflows. Develop complex Salesforce Flows to automate business processes. Write, test, and deploy Apex code (classes, triggers, and components) to extend Salesforce functionality. Participate … full software development lifecycle, including requirements gathering, development, testing, deployment, and maintenance. Implement and maintain robust DevOps practices, including source code management, branching strategies, pull requests, and commits. Utilize DevOps tools such as [Specify: Copado, Gearset, Azure DevOps, or others] for deployment and release management. Work within ...

write sql stored procedure. TLM database table linkages, for analyzing production issue from the backend. Expertise in the exception management and breaks allocation automation on the TLM platform Expertise in Unix shell scripting should be well versed with the most frequently used UNIX commands and the Vi Editor. Well … Very good communication skills to convey clear details to end users/clients for any challenges faced during build or testing. Knowledge of automated deployment tools will be an added advantage. What you will need to succeed in the role: Advance knowledge working with TLM TOOLS as SMART STUDIO ...

scalable, reliable, and secure applications. Build, support, and integrate web applications, microservices, and data pipelines with high code quality. Write automated unit, integration, and deployment tests. Use CI/CD tooling (e.g., GitLab Runners) to build and deploy code across environments. Apply modern development methodologies; use JIRA for project … code. Excellent problem‐solving, communication, and teamwork skills. Self‐starter with entrepreneurial attitude, willingness to mentor, and thrive in fast‐paced environments. Experience with automation testing and performance testing. Fixed‐income front‐office trading systems experience preferred. Bachelor’s degree in Computer Science, Engineering, or related field. Equal Opportunity ...

looking at SC Cleared Azure DevOps Engineer to support the delivery of large-scale, cloud-based data platform. Key Responsibilities: Build and maintain automated deployment pipelines within Azure environments Develop and manage Azure infrastructure using Infrastructure as Code Implement monitoring and alerting solutions to improve platform reliability Ensure security … compliance and governance controls are embedded across the platform Support deployment, testing and environment management activities Collaborate with engineering teams to improve platform performance and delivery Produce technical documentation Requirements Experience working as a DevOps Engineer within a large, enterprise environment Strong Azure DevOps experience Active SC Clearance Experience ...

pipelines. Assist with maintaining service accounts, IAM roles, and organisational policies following least-privilege principles. Support with application migration activities including the technical analysis, deployment and testing alongside the architecture teams. Develop and maintain documentation including Low Level Designs, runbooks and guidance. What You'll Bring Proven hands … knowledge of Google Distributed Cloud (GDC), Experience working in environments without direct internet connectivity. Strong engineering background with deep understanding of IaC (Terraform, Deployment Manager), automation, and CI/CD pipelines. Expertise in networking, IAM, containerisation (GKE/Kubernetes), and secure systems design. Confident working within highly regulated ...

This role combines deep technical expertise with business understanding, requiring end-to-end ownership of AI and machine learning solutions from problem definition through deployment, monitoring, and impact measurement. Key Responsibilities Design and develop production-grade AI and machine learning solutions across the sales data platform. Build recommendation engines … machine learning capabilities into enterprise applications. Own the end-to-end AI/ML lifecycle, including problem definition, data exploration, model development, validation, deployment, and monitoring. Develop forecasting models, segmentation strategies, optimisation algorithms, and early warning systems to support sales performance and decision-making. Collaborate with engineering, sales operations ...

DevOps efficiency through innovation, agility and cost optimisation. Take a holistic approach to modernising the developer experience, focusing on organisational culture, DevOps practices, processes, automation and tooling. Architect scalable and resilient cloud infrastructure to ensure the seamless deployment and optimisation of containerised applications. Collaborate with cross-functional teams … implement automation strategies that reduce operational complexity and drive continuous improvement. The Requirements Strong understanding of the SRE mindset and principles, including the creation and management of Service Level Indicators (SLIs), Service Level Objectives (SLOs) and error budgets ensuring reliability and performance. Experience in implementing observability, instrumenting applications ...

Develop and integrate RESTful APIs for seamless communication between systems and services Work across the full SDLC pipeline (design, development, testing, CI/CD, deployment, and maintenance) Collaborate with cross-functional teams to translate business requirements into technical solutions Ensure best practices in coding, version control, testing, and deployment ...

production environments • Solid engineering foundations (Python and modern data/ML ecosystems) • Familiarity with cloud-based AI platforms and scalable data systems • Experience with deployment practices (automation, monitoring, reliability, etc.) • Ability to operate in ambiguity and guide decision-making with structure and clarity This is a client-facing ...