{"id":3201770,"url":"https://alion.io/job/brillio-ai-automation-coe-lead-infrastructure-engineering","title":"AI & Automation COE Lead - Infrastructure Engineering","company":{"id":3063,"name":"Brillio","domain":"brillio.com","url":"https://alion.io/company/brillio","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":76,"open_postings":43,"ghost_share":0,"stale_share":0.953,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":57000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":7,"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":"Ansible","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Datadog","optional":false},{"name":"Dynatrace","optional":false},{"name":"GCP","optional":false},{"name":"Incident Management","optional":false},{"name":"ITSM","optional":false},{"name":"New Relic","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PowerShell","optional":false},{"name":"Python","optional":false},{"name":"Self-Healing","optional":false},{"name":"Service Desk","optional":false},{"name":"Splunk","optional":false},{"name":"Terraform","optional":false},{"name":"Agile","optional":true},{"name":"ITIL","optional":true}],"status":"live","first_seen_at":"2026-10-24T08:23:43Z","employer_posted_date":null,"last_verified_at":"2026-10-24T08:23:43Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"Role : AI & Automation CoE Lead - Infrastructure Engineering\n\nRole Overview : \n\nWe are seeking a strategic and hands-on AI & Automation CoE Lead to establish and drive the Artificial Intelligence and Automation Center of Excellence (CoE) within Infrastructure Engineering. The role will be responsible for defining the automation vision, building reusable frameworks, accelerating AI adoption, driving operational excellence, and enabling next-generation Infrastructure, Cloud, Platform, and Managed Services delivery through AI-led transformation.\n\nThe ideal candidate will combine expertise in Infrastructure Engineering, Cloud Platforms, Automation, AIOps, GenAI, Platform Engineering, and Service Operations to improve efficiency, reliability, scalability, and business outcomes.\n\nKey Responsibilities : \n\nAI & Automation Strategy : \n\n- Define and implement the AI & Automation roadmap for Infrastructure Engineering.\n\n- Establish governance, standards, reusable frameworks, and best practices.\n\n- Identify high-value automation and AI use cases across Infrastructure Operations, Cloud Services, Security, and Platform Engineering.\n\n- Drive enterprise-wide adoption of AI-driven operational models.\n\nAutomation & Engineering Excellence : \n\n- Lead development of automation solutions using Infrastructure as Code (IaC), orchestration, and self-healing capabilities.\n\n- Build reusable automation assets for provisioning, monitoring, patching, remediation, security, and cloud operations.\n\n- Drive adoption of Terraform, Ansible, PowerShell, Python, Azure Automation, AWS Automation, and CI/CD pipelines.\n\n- Enable Infrastructure Platform Engineering and self-service operational capabilities.\n\nAI & AIOps Transformation : \n\n- Implement AIOps, predictive analytics, anomaly detection, event correlation, and intelligent incident management solutions.\n\n- Drive GenAI-based use cases including Service Desk Virtual Assistants, Knowledge Automation, Runbook Generation, Incident Summarization, Root Cause Analysis Assistance, and Automated Documentation.\n\n- Integrate AI capabilities into ITSM, ITOM, and service management workflows.\n\nCloud & Infrastructure Modernization : \n\n- Accelerate AI-led Cloud Migration, Infrastructure Modernization, and Operations Transformation initiatives.\n\n- Drive automation across AWS, Azure, GCP, Hybrid Cloud, Network, Compute, Storage, and Security platforms.\n\n- Collaborate with Architecture, SRE, Cloud, and Security teams to improve operational resilience and efficiency.\n\nInnovation & CoE Leadership : \n\n- Build and manage the AI & Automation Center of Excellence.\n\n- Lead innovation programs, proof of concepts, accelerators, and intellectual property development.\n\n- Establish automation maturity models, KPI frameworks, and value realization tracking.\n\n- Mentor engineering teams and build next-generation AI and Automation capabilities across the organization.\n\nRequired Skills & Experience : \n\n- 12+ years in Infrastructure Engineering, Cloud Operations, or Managed Services.\n\n- 5+ years driving enterprise automation and transformation initiatives.\n\n- Strong expertise in Infrastructure Automation, Cloud Platforms (AWS/Azure/GCP), Terraform, Ansible, Python, PowerShell, DevOps & CI/CD, Platform Engineering, ITSM/ITOM, and Observability & Monitoring Platforms.\n\n- Experience with AIOps platforms such as Dynatrace, Datadog, Moogsoft, Splunk, New Relic, or similar.\n\n- Working knowledge of GenAI, LLMs, Copilot technologies, AI agents, and AI-powered operations.\n\n- Strong stakeholder management, solution consulting, and leadership skills.\n\nPreferred Qualifications : \n\n- AWS/Azure Cloud Certifications\n\n- Terraform Associate\n\n- ITIL\n\n- PMP / Agile Certifications\n\n- AI/ML or Generative AI Certifications\n\nSuccess Metrics : \n\n- Automation-led effort reduction and productivity gains\n\n- Reduction in MTTR and incident volumes\n\n- Improved service reliability and operational efficiency\n\n- Increased automation coverage across infrastructure services\n\n- AI-driven innovation adoption and business value realization\n\n- Creation of reusable accelerators, assets, and intellectual property\nSkills\nAIOps, IAC Terraform, Ansible, 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