{"id":2811702,"url":"https://alion.io/job/hcltech-senior-technical-specialist-93","title":"Senior Technical Specialist","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Sales","role_family":"Sales","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Romania"],"countries":["RO"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":27000,"max_usd":69000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":7498},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AIOps","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bicep","optional":false},{"name":"ChatGPT","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Databricks","optional":false},{"name":"Digital Twin","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Incident Management","optional":false},{"name":"LLMOps","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Power BI","optional":false},{"name":"PowerShell","optional":false},{"name":"Python","optional":false},{"name":"Self-Healing","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-18T09:43:47Z","employer_posted_date":"2026-10-18","last_verified_at":"2026-10-24T17:33:32Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Job Summary\nJob Description: Lead DevOps Engineer (Data & AI Platform)\nAbout the Role\nAt Anglo American, we are advancing a world-class data and AI platform that powers decision-making across the entire mining value chain. Built on Azure and Databricks, our platform enables scalable data products, advanced analytics, and emerging AI capabilities-from digital twins to intelligent automation and natural language querying.\nWe are looking for a Lead DevOps Engineer to play a critical role in evolving our platform into a highly automated, AI-enabled delivery ecosystem. This role goes beyond traditional DevOps-focusing on platform engineering, AI-assisted development, and intelligent automation of software delivery and operations.\nYou will lead the design and implementation of modern DevOps practices, integrating AI tools, copilots, and automation frameworks to significantly improve developer productivity, pipeline efficiency, and platform reliability.\nRole Overview\nAs a Lead DevOps Engineer, you will refine and enhance CI/CD processes, integrate new capabilities into release pipelines, and drive automation across the software delivery lifecycle. You will also play a key role in embedding AI-driven practices into DevOps, enabling faster and more reliable delivery of data and AI products.\nYou will work closely with data engineers, platform teams, and product teams to ensure seamless, scalable, and intelligent deployment processes across the Anglo American Data Platform.\nKey Responsibilities\nKey Responsibilities\nDevOps Strategy and Platform Evolution\nDefine and implement a modern DevOps and platform engineering strategy aligned with data and AI platform goals. \nDevelop roadmaps that incorporate AI-assisted development, testing, and operations. \nDrive the evolution from traditional DevOps to intelligent, self-service platform capabilities. \nContinuously evaluate emerging technologies (e.g., GenAI, LLMOps, AIOps) and incorporate them where relevant. \nAI-Enabled CI/CD and Automation\nDesign and optimize CI/CD pipelines using AI-assisted tools (e.g., code generation, test generation, pipeline optimization). \nIntegrate AI copilots and automation agents into development and deployment workflows. \nImplement intelligent quality gates (e.g., automated code reviews, anomaly detection in pipelines). \nEnable self-healing pipelines and automated failure diagnostics where possible\nAutomation and Framework Enhancement\nBuild scalable automation frameworks leveraging AI, scripting, and infrastructure as code. \nAutomate repetitive tasks using AI agents, prompt-based workflows, or orchestration frameworks. \nEnhance DevOps pipelines to support data products and AI/ML workloads (MLOps/LLMOps).\nStandardize reusable templates and pipeline components for platform-wide adoption. \nData & AI Platform Integration\nAnalyze and optimize integrations across the Anglo American Data Platform, including: \nDatabricks (data processing, workflows, DABs) \nAirflow (orchestration) \nAzure services (compute, storage, identity) \nPower BI / downstream consumption layers \nSupport deployment patterns for AI/ML models, feature pipelines, and inference services.\nEnable end-to-end lifecycle management for AI applications (training → deployment → monitoring). \nGovernance, Security, and Reliability\nImplement governance practices across pipelines, including policy-as-code and automated compliance checks. \nManage access control and ensure secure DevOps practices across environments. \nIntroduce AIOps practices for monitoring, alerting, and incident management. \nEnsure high availability, scalability, and observability of DevOps processes. \nSkill Requirements\nTechnical Expertise\nStrong experience with CI/CD tools (e.g., Azure DevOps, GitHub Actions). \nExpertise in infrastructure as code (Bicep, ARM or similar). \nProficiency in scripting (PowerShell, Python, Bash). \nDeep understanding of DevOps principles, Git workflows, and release strategies. \nExperience with Azure services and cloud-native architectures. \nFamiliarity with data platforms (Databricks, ADF, Airflow, SQL, AAS or equivalent). \nAI & Modern DevOps Capabilities\nHands-on experience or strong familiarity with: \n AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, code assistants) \n MLOps / LLMOps concepts (model deployment, monitoring, versioning) \n AIOps tools for monitoring and incident management \nUnderstanding of how AI can be applied to: \nCode generation and testing \nPipeline optimization \nIncident detection and resolution \nExperience integrating APIs or services for AI capabilities into workflows is a plus\nOther Requirements\nnull","description_format":"text","description_chars":4625,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems 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