{"id":1350545,"url":"https://alion.io/job/jman-group-devops-ai-engineer","title":"Devops AI Engineer","company":{"id":2353096,"name":"JMAN Group","domain":"jmangroup.com","url":"https://alion.io/company/jmangroup","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"OpenAI","optional":false},{"name":"Terraform","optional":false},{"name":"Azure AKS","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"Platform Engineering","optional":true},{"name":"PowerShell","optional":true},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-09-27T17:24:17Z","employer_posted_date":null,"last_verified_at":"2026-09-27T17:24:17Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"ABOUT JMAN:\nJMAN Groupis a fast-growing data engineering & data science consultancy. We work primarily with Private Equity Funds and their Portfolio Companies to create commercial value using Data & Artificial Intelligence. In addition, we also work with growth businesses, large corporates, multinationals, and charities.\n\nWe are headquartered in London with Offices in New York, London and Chennai. Our team of over 450 people is a unique blend of individuals with skills across commercial consulting, data science and software engineering.\n\nWe were founded by cousins Anush Newman (Co-founder & CEO) and Leo Valan (Co-founder & CTO) and have grown rapidly since 2019. In May 2023 we took a minority investment from Baird Capital and in January 2024 we opened an office in New York with the ambition of growing our US business to be as large as, if not bigger than, our European business by 2027.\n\nWhy work at JMAN:\nOur 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.\nCurrent Benefits:\n− Competitive annual bonus\n− Market-leading private health insurance\n− Regular company socials\n− Annual company away days\n− Extensive training opportunities\n\nKey Responsibilities:\n\nBuild and operate cloud infrastructure on Azure to support application and data platform environments.\nImplement infrastructure using Infrastructure as Code (IaC) tools such as Terraform, ensuring consistent, reliable, and repeatable deployments.\nDesign, build, and maintain CI/CD pipelines using tools such as Azure DevOps or GitHub Actions for automated build and deployment processes.\nManage source control (Git) workflows, including branching strategies, versioning, and release management.\nDeploy and manage application and platform workloads on Azure, ensuring reliability, scalability, and availability.\nDeploy, 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.\nBuild and maintain automated deployment pipelines for AI/ML and Generative AI workloads, including environment configuration, access management, monitoring, scalability, governance, and operational reliability.\nSupport the deployment, operationalisation, and lifecycle management of Large Language Model (LLM) based solutions, ensuring production readiness, platform reliability, security, and scalability.\nExposure 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.\nCollaborate directly with Data Science, AI Engineering, Analytics, and Software Engineering teams to enable secure deployment and operation of AI-enabled applications and services.\nImplement and manage containerised workloads using Docker and Kubernetes (AKS).\nManage and optimise cloud infrastructure across environments, ensuring performance, cost efficiency, and reliability.\nConfigure and maintain monitoring, logging, and alerting systems to ensure platform observability and proactive issue detection.\nMaintain clear documentation for infrastructure, pipelines, deployment processes, and platform standards.\n\nSkills & Qualifications\nBachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent industry experience.\n4+ years of experience in DevOps, Platform Engineering, or Cloud Infrastructure, with practical experience supporting AI/ML, Data, and Generative AI platforms.\nStrong proficiency in Microsoft Azure, including compute, networking, storage, security, and AI services, with experience deploying and managing cloud-native applications and AI-enabled solutions.\nAzure certification (AZ-104 or AZ-400 equivalent) are considered an added advantage and valued as evidence of practical cloud platform knowledge.\nStrong experience with Infrastructure as Code (Terraform preferred).\nHands-on experience with CI/CD tools such as Azure DevOps, GitHub Actions, or similar.\nStrong understanding of Git-based workflows, including branching, version control, and release strategies.\nDemonstrated commitment to continuous learning through certifications, labs, technical communities, hackathons, or hands-on experimentation with modern cloud and AI technologies.\nProficiency in scripting (PowerShell, Bash, or Python) specifically tailored for infrastructure and AI automation tasks.\nStrong problem-solving skills and ability to work independently.\n\nBehavioural Competencies\nAt JMAN, we expect our team members to embody the following:\nProactive and accountable in driving platform readiness\nAdaptable and comfortable with ambiguity\nStrong collaborator across engineering and consulting teams\nCommitted to continuous improvement, learning, and technical upskilling\nProfessional, reliable, and delivery-focused\nCurious and adaptable towards emerging technologies, including AI-assisted engineering and automation practices.","description_format":"text","description_chars":5208,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning","Equity","Health insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Analytics & BI Consulting","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-09-27T18:01:51Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring 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