
Agentic AI Systems Lead
LTM · Bengaluru, Karnataka, India
- Full-time
- Posted 17 days ago
Job description
We are seeking a highly experienced Agentic AI Systems Lead to architect, govern, and scale enterprise-wide Agentic AI ecosystems that power next-generation AI Ops, Autonomous IT Operations, Intelligent Automation, and AI-driven Service Management platforms. This role will be responsible for defining the architecture, governance, orchestration, and operational framework for enterprise-scale multi-agent systems, enabling autonomous decision-making, intelligent workflow execution, self-healing operations, predictive incident management, and AI-powered operational excellence. The ideal candidate will possess deep expertise in Agentic AI architectures, Multi-Agent Systems, AI Orchestration Platforms, AI Ops, Generative AI, Enterprise Architecture, and Autonomous Operations, with proven experience leading large-scale transformations across global enterprises. The candidate will partner with CIOs, CTOs, Enterprise Architects, IT Operations Leaders, AI Engineering teams, Data Architects, and Platform Engineering teams to build resilient, secure, and scalable AI-powered operating models.
Key Responsibilities
- Enterprise Agentic AI Strategy
Define enterprise-wide Agentic AI vision, roadmap, and adoption strategy. Establish operating models for AI-powered autonomous operations. Drive enterprise transformation from traditional automation to Agentic AI-driven decision systems. Develop reusable frameworks, reference architectures, and best practices for AI agent deployment.
- Multi-Agent Systems Architecture
Design and govern enterprise-scale multi-agent ecosystems. Define standards and architectural patterns for: Autonomous Agents Interactive Agents Supervisor Agents Orchestrator Agents Domain-Specific Agents AI Copilots AI Operations Agents
- Establish communication, collaboration, and coordination mechanisms across agents.
- Define agent lifecycle management, agent governance, and operational controls.
- Agent Architecture Design
Autonomous Agents Design self-directed agents capable of independently executing operational tasks. Enable agents to perform incident resolution, remediation, optimization, and decision support. Build self-healing and autonomous operational capabilities. Interactive Agents Design conversational and task-oriented agents supporting human-in-the-loop workflows. Enable intelligent collaboration between users and AI systems. Architect enterprise AI assistants and virtual operations support agents. Supervisor Agents
- Define agent governance and oversight mechanisms.
Implement monitoring, auditing, validation, and compliance controls. Design supervisory frameworks for risk management and operational safety. Design coordination frameworks enabling interaction among multiple agents. Architect intelligent workflow orchestration and multi-agent collaboration models. Manage task decomposition, delegation, and execution monitoring.
- Architect specialized agents supporting:
IT Operations Service Management Cloud Operations Security Operations Infrastructure Management Business Operations
- Create reusable domain intelligence models and knowledge assets.
- Design enterprise AI copilots supporting:
ITSM Operations Service Desk Operations Engineering Teams Operations Teams Business Functions Enable contextual assistance, recommendations, knowledge retrieval, and guided decision-making. AI Operations Agents
- Architect autonomous operations agents capable of:
Event Correlation, Incident Analysis, Root Cause Analysis, Remediation Automation, Change Risk Assessment, Capacity Optimization, Service Health Monitoring, AI Ops & Autonomous Operations
- Lead implementation of AI-driven operational intelligence platforms.
- Design autonomous operational workflows and decision engines.
- Enable predictive operations and proactive incident prevention.
- Architect self-healing and closed-loop remediation frameworks.
- Drive adoption of intelligent event management and operational automation.
- Generative AI & Agentic AI Platforms
- Define architectures integrating:
Large Language Models (LLMs) Agent Frameworks Knowledge Graphs Vector Databases Retrieval-Augmented Generation (RAG) Enterprise Knowledge Systems Architect enterprise-grade reasoning and planning systems.
- Establish AI safety, explainability, and governance controls.
Must-Have Technical Skills
Agentic AI Architecture
Multi-Agent System Design Autonomous Agent Frameworks AI Agent Orchestration AI Workflow Automation Cognitive Architecture Design AI Reasoning Systems Agent Governance Frameworks AI Agent Categories Autonomous Agents Interactive Agents Supervisor Agents Orchestrator Agents AI Copilots AI Operations Agents AI Technologies Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Knowledge Graphs Vector Databases Semantic Search AI Decision Systems AI Ops & Operations AIOps Platform Architecture Autonomous Operations Intelligent Automation Incident Intelligence Event Management Root Cause Analysis Self-Healing Operations Operational Analytics Enterprise Architecture Distributed Systems Cloud-Native Architecture Microservices Architecture API-First Design Event-Driven Architecture Enterprise Integration Patterns
About the company

LTM — a Larsen & Toubro company — is an AI-centric global technology services company and the Business Creativity partner to the world’s largest enterprises. We bring human insights and intelligent systems together to help clients create greater value at the intersection of technology and domain expertise. Our capabilities span integrated operations, transformation, and business AI — enabling new ways of working, new productivity paradigms, and new roads to value. Together with over 87,000 employees across 40 countries and our global network of partners, LTM owns business outcomes for our clients, helping them not just outperform the market, but to Outcreate it.
- Headquarters
- Bengaluru, Karnataka, India
- Company size
- 28868
- Industry
- IT Services and IT Consulting
- Website
- ltm.com