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

📌 Agentic AI Systems Lead (Bengaluru)
🏢 LTM
📍 Bengaluru