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AI Tech Lead

Virtusa · Bangalore Urban, Karnataka, India

~₹35L (est.)8–15 yrs experiencefull_timePosted 1w ago
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Job description

**AI Tech Lead** **Mandatory Skills** generative ai,Python,AWS,Enterprise Architecture,Agentic Ai,Model Context Protocol (MCP) **Job Description** - Enterprise Experience 6+ years of experience managing technical IT projects, with a strong emphasis on IT Service Management (ITSM), Application Management Services (AMS), or enterprise software delivery. - Generative AI Competency Proven architectural understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) , and system token optimization. - Integration Expertise Hands-on experience or profound structural knowledge of connecting conversational layers to enterprise backend systems (specifically SAP S/4HANA via APIs, JIRA, and BMC Helix environments). - Protocol & Security Familiarity Conceptual grasp of modern AI connectivity paradigms like Model Context Protocol (MCP), vector databases, and enterprise data masking methodologies. - Framework Orientation Familiarity with global AI governance standards (e.g., NIST AI RMF, ISO/IEC 42001) is highly desirable . **Education Qualificaiton** B-Tech or Equivalent Engineering Degree **Roles & Responsibilities** **Key Responsibilities** - Solution Adoption & Implementation Ownership - Drive AI Adoption Lead the end-to-end adoption roadmap of the enterprise AI solution across multiple projects, platforms, and geographic regions. - Proof of Concept to Production Lifecycle Own the execution of complex Generative AI use cases from initial validation to full production deployment, specifically optimizing automated Level 1 (L1) support workflows and Level 0 (L0) automated system remediation infrastructure. - Value Optimization & Metrics Set and actively pursue project-level performance optimization KPIs, focusing on reducing Mean Time to Resolution (MTTR) , maximizing ticket deflection rates, and containing operational support costs . - Use Case Ideation Continuously identify, evaluate, and prioritize high-impact AI opportunities to systematically reduce IT helpdesk workloads and bottlenecks .