DevOps Engineer

£400-£500pd Inside IR35

Initial 6 month engagement

2 days on site in London

emagine is a high-end professional services consultancy and solutions firm specialising in providing business and technology services to the financial services sector, we power progress, solve challenges and deliver real results through tailored high-end consulting services and solutions.

 

We have created a culture of openness and integrity by building genuine and strong relationships and partnerships, enabling us to be uncompromising in our dedication in delivering the optimal service for our clients. Our commitment is not just towards our clients but we aim to foster a positive and equitable working environment with our consultants and colleagues which stems from our core values: Confident, Dedicated, Responsible, Genuine.

We are seeking an experienced DevOps Engineer to play a key role in supporting and scaling a modern multi-cloud infrastructure across Azure and AWS. Working closely with backend, full stack, data engineering and platform teams, you will be responsible for building and maintaining the infrastructure, automation, governance and deployment capabilities that enable efficient, secure and reliable software delivery.

This is an exciting opportunity to join a fast-paced, collaborative engineering environment where you'll have a direct impact on platform reliability, developer productivity, cloud operations, and the adoption of modern AI-enabled engineering practices.

Key Responsibilities

• Design, build and maintain infrastructure-as-code solutions using Terraform.

• Manage, optimise and support cloud environments across Microsoft Azure and AWS.

• Build, enhance and maintain CI/CD pipelines that support multiple engineering teams.

• Collaborate with backend, full stack and Databricks engineers to ensure smooth deployments and effective environment management.

• Drive automation initiatives and implement reliability improvements across the platform.

• Monitor, troubleshoot and continuously improve infrastructure performance, scalability and security.

• Design and implement cloud governance, observability and security controls across multi-cloud environments.

• Support Kubernetes-based platforms and cloud-native applications, ensuring high availability, resilience and operational excellence.

• Champion the adoption of AI-assisted engineering practices, leveraging tools such as GitHub Copilot, ChatGPT, Cursor or similar technologies to improve productivity, automation and developer experience.

• Contribute to platform standards, engineering best practices and infrastructure architecture decisions.

Essential Skills & Experience

• Proven hands-on experience with Terraform (essential).

• Strong working knowledge of Azure with experience in AWS environments.

• Experience designing and managing CI/CD pipelines and deployment automation.

• Strong understanding of DevOps best practices, cloud infrastructure and platform engineering.

• Experience working with Kubernetes platforms such as AKS, EKS or OpenShift.

• Demonstrable experience using AI-assisted engineering tools (e.g. GitHub Copilot, Cursor, ChatGPT, Claude or similar) within day-to-day engineering workflows.

• Ability to articulate how AI has been used to improve software delivery, automation, troubleshooting, infrastructure management or developer productivity.

• Strong understanding of observability, monitoring and operational excellence principles.

• Ability to work effectively within a cross-functional, agile delivery environment.

• Excellent problem-solving and communication skills.

• Experience working alongside backend, full stack, platform or data engineering teams.

• Exposure to Databricks environments.

• Knowledge of scripting or automation languages such as Python, Bash or PowerShell.

• Experience with additional cloud-native technologies and services.

Desirable Experience

• Experience with spec-driven development approaches, including GitHub Spec Kit, OpenSpec, OpenAPI, contract-first development, Architecture Decision Records (ADRs) or similar methodologies.

• Exposure to AI Platform Engineering or MLOps, including model deployment pipelines, model serving, AI infrastructure, Azure Machine Learning, SageMaker, Vertex AI, Kubeflow, MLflow or similar technologies.

• Experience supporting AI, machine learning, LLM or agentic workloads in cloud-native environments.

• Experience implementing observability, governance and security controls for AI-powered applications and autonomous systems.

• Knowledge of platform engineering, policy-as-code, cloud governance and security automation frameworks.

Working Environment

• Modern multi-cloud environment utilising Azure and AWS.

• Collaborative team structure with close interaction across platform, software, data and cloud engineering teams.

• Fast-paced, delivery-focused culture with opportunities to influence platform strategy, automation practices and AI-enabled engineering initiatives.

• Hybrid working model with 2 days per week in the office.

Interested?

 

At emagine, we are committed to building an international and diverse team by embracing our different backgrounds.

 

If you are up to the challenge and would like to find out more, get in touch with us immediately, our internal recruitment team is always keen to hear from dynamic individuals that are looking to further their career and explore their full potential. 

 

“emagine is an equal opportunity employer, and employment practices are based strictly on merit. It is the policy of the Company to give equal opportunity in employment regardless of sex, sexual orientation, marital status, race, age, disability, gender reassignment, pregnancy and maternity, religion or ethnic origin”