ABOUT JMAN:
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JMAN Group is a growing technology-enabled management consultancy that empowers organizations to create value through data.
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Founded in 2010, we are a team of 600+ consultants based in London, UK, and a team of 450+ engineers in Chennai, India. Having delivered multiple projects in the US, we are now opening a new office in New York to help us support and grow our US client base.
- We approach business problems with the mindset of a management consultancy and the capabilities of a tech company. We work across all sectors, and have in depth experience in private equity, pharmaceuticals, government departments and high-street chains.
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Our team is as cutting edge as our work. We take pride for ourselves on being great to work with – no jargon or corporate-speak, flexible to change and receptive of feedback.
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We have a huge focus on investing in the training and professional development of our team, to ensure they can deliver high quality work and shape our journey to becoming a globally recognised brand. The business has grown quickly in the last 3 years with no signs of slowing down. "
Why work at JMAN:
Our vision is to ensure JMAN Group is the passport to our team’s future. We want our team to go on a fast-paced, high-growth journey with us – when our people want to do something else, the skills, training, exposure, and values that JMAN has instilled in them should open doors all over the world.
Current Benefits:
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Competitive annual bonus
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Market-leading private health insurance
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Regular company socials
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Annual company away days
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Extensive training opportunities
Skills & Qualifications
- Bachelor's degree in computer science, Engineering, Information Technology, or a related field, or equivalent industry experience.
- 2–5 years of experience in DevOps, Platform Engineering, or Cloud Infrastructure, with practical experience supporting AI/ML, Data, and Generative AI platforms.
- Strong proficiency in Microsoft Azure, including compute, networking, storage, security, and AI services, with experience deploying and managing cloud-native applications and AI-enabled solutions.
- Azure certification (AZ-104 or AZ-400 equivalent) are considered an added advantage and valued as evidence of practical cloud platform knowledge.
- Strong experience with Infrastructure as Code (Terraform preferred).
- Hands-on experience with CI/CD tools such as Azure DevOps, GitHub Actions, or similar.
- Strong understanding of Git-based workflows, including branching, version control, and release strategies.
- Demonstrated commitment to continuous learning through certifications, labs, technical communities, hackathons, or hands-on experimentation with modern cloud and AI technologies.
- Proficiency in scripting (PowerShell, Bash, or Python) specifically tailored for infrastructure and AI automation tasks.
- Strong problem-solving skills and ability to work independently.
Key Responsibilities:
- Build and operate cloud infrastructure on Azure to support application and data platform environments.
- Implement infrastructure using Infrastructure as Code (IaC) tools such as Terraform, ensuring consistent, reliable, and repeatable deployments.
- Design, build, and maintain CI/CD pipelines using tools such as Azure DevOps or GitHub Actions for automated build and deployment processes.
- Manage source control (Git) workflows, including branching strategies, versioning, and release management.
- Deploy and manage application and platform workloads on Azure, ensuring reliability, scalability, and availability.
- Deploy, configure, and manage AI platform environments such as Azure AI Foundry, Azure OpenAI, Azure Machine Learning, and related cloud-native AI services, supporting AI, analytics, and Generative AI workloads.
- Build and maintain automated deployment pipelines for AI/ML and Generative AI workloads, including environment configuration, access management, monitoring, scalability, governance, and operational reliability.
- Support the deployment, operationalisation, and lifecycle management of Large Language Model (LLM) based solutions, ensuring production readiness, platform reliability, security, and scalability.
- Exposure to configuring and managing modern data platform environments, including Azure Databricks and Microsoft Fabric, to support downstream AI and analytics workloads, is good to have.
- Collaborate directly with Data Science, AI Engineering, Analytics, and Software Engineering teams to enable secure deployment and operation of AI-enabled applications and services.
- Implement and manage containerised workloads using Docker and Kubernetes (AKS).
- Manage and optimise cloud infrastructure across environments, ensuring performance, cost efficiency, and reliability.
- Configure and maintain monitoring, logging, and alerting systems to ensure platform observability and proactive issue detection.
- Maintain clear documentation for infrastructure, pipelines, deployment processes, and platform standards.
Preferred Qualifications
- Experience with Azure Databricks platform setup or environment management.
- Familiarity with Microsoft Fabric platform setup or administration.
- Exposure to Kubernetes (AKS) for container orchestration.
- Exposure to data platforms or analytics workloads from a DevOps perspective.
- Familiarity with agile delivery models and working with cross-functional teams.
- Experience with AWS cloud platform.
Behavioural Competencies
At JMAN, we expect our team members to embody the following:
- Proactive and accountable in driving platform readiness
- Adaptable and comfortable with ambiguity
- Strong collaborator across engineering and consulting teams
- Committed to continuous improvement and learning
- Professional, reliable, and delivery-focused
