Bangalore, Karnataka
Job Summary

"Role Overview: Design, architect, and deploy agent-based AI solutions that autonomously plan, reason, and execute complex tasks for enterprise operations. Guide clients through the full lifecycle of Agentic AI adoption—from strategy and platform selection to deployment, integration, and ongoing optimization. Collaborate with cross-functional teams to deliver robust, scalable AI solutions for business observability, IT operations, and process automation.

Key Responsibilities

"Role Overview: Design, architect, and deploy agent-based AI solutions that autonomously plan, reason, and execute complex tasks for enterprise operations. Guide clients through the full lifecycle of Agentic AI adoption—from strategy and platform selection to deployment, integration, and ongoing optimization. Collaborate with cross-functional teams to deliver robust, scalable AI solutions for business observability, IT operations, and process automation.

Key Responsibilities:

- Analyze business use cases and design detailed Agentic AI solution architectures.
- Lead integration of LLMs (e.g., GPT-4, Claude, LLaMA) and agentic frameworks (LangChain, CrewAI, AutoGen, Semantic Kernel) into enterprise workflows.
- Implement Retrieval-Augmented Generation (RAG) pipelines and connect agents to enterprise knowledge systems.
- Develop agent-to-agent communication protocols and multi-agent coordination.
- Own configuration, conversational design, prompting, testing, and deployment of AI agents across digital and voice channels.
- Ensure compliance with security, governance, and Responsible AI principles (RBAC, data privacy, auditability).
- Facilitate workshops, technical deep-dives, and executive briefings to align stakeholders.
- Track, report, and optimize key success metrics (cost savings, accuracy, customer satisfaction, retention)."

"Role Overview: Design, architect, and deploy agent-based AI solutions that autonomously plan, reason, and execute complex tasks for enterprise operations. Guide clients through the full lifecycle of Agentic AI adoption—from strategy and platform selection to deployment, integration, and ongoing optimization. Collaborate with cross-functional teams to deliver robust,



scalable AI solutions for business observability, IT operations, and process automation.

Key Responsibilities:

- Analyze business use cases and design detailed Agentic AI solution architectures.
- Lead integration of LLMs (e.g., GPT-4, Claude, LLaMA) and agentic frameworks (LangChain, CrewAI, AutoGen, Semantic Kernel) into enterprise workflows.
- Implement Retrieval-Augmented Generation (RAG) pipelines and connect agents to enterprise knowledge systems.
- Develop agent-to-agent communication protocols and multi-agent coordination.
- Own configuration, conversational design, prompting, testing, and deployment of AI agents across digital and voice channels.
- Ensure compliance with security, governance, and Responsible AI principles (RBAC, data privacy, auditability).
- Facilitate workshops, technical deep-dives, and executive briefings to align stakeholders.
- Track, report, and optimize key success metrics (cost savings, accuracy, customer satisfaction, retention)."

Skill Requirements

"Role Overview: Design, architect, and deploy agent-based AI solutions that autonomously plan, reason, and execute complex tasks for enterprise operations. Guide clients through the full lifecycle of Agentic AI adoption—from strategy and platform selection to deployment, integration, and ongoing optimization. Collaborate with cross-functional teams to deliver robust, scalable AI solutions for business observability, IT operations, and process automation.

Key Responsibilities:

- Analyze business use cases and design detailed Agentic AI solution architectures.
- Lead integration of LLMs (e.g., GPT-4, Claude, LLaMA) and agentic frameworks (LangChain, CrewAI, AutoGen, Semantic Kernel) into enterprise workflows.
- Implement Retrieval-Augmented Generation (RAG) pipelines and connect agents to enterprise knowledge systems.




- Develop agent-to-agent communication protocols and multi-agent coordination.
- Own configuration, conversational design, prompting, testing, and deployment of AI agents across digital and voice channels.
- Ensure compliance with security, governance, and Responsible AI principles (RBAC, data privacy, auditability).
- Facilitate workshops, technical deep-dives, and executive briefings to align stakeholders.
- Track, report, and optimize key success metrics (cost savings, accuracy, customer satisfaction, retention)."

"Role Overview: Design, architect, and deploy agent-based AI solutions that autonomously plan, reason, and execute complex tasks for enterprise operations. Guide clients through the full lifecycle of Agentic AI adoption—from strategy and platform selection to deployment, integration, and ongoing optimization. Collaborate with cross-functional teams to deliver robust, scalable AI solutions for business observability, IT operations, and process automation.

Key Responsibilities:

- Analyze business use cases and design detailed Agentic AI solution architectures.
- Lead integration of LLMs (e.g., GPT-4, Claude, LLaMA) and agentic frameworks (LangChain, CrewAI, AutoGen, Semantic Kernel) into enterprise workflows.
- Implement Retrieval-Augmented Generation (RAG) pipelines and connect agents to enterprise knowledge systems.
- Develop agent-to-agent communication protocols and multi-agent coordination.
- Own configuration, conversational design, prompting, testing, and deployment of AI agents across digital and voice channels.
- Ensure compliance with security, governance, and Responsible AI principles (RBAC, data privacy, auditability).
- Facilitate workshops, technical deep-dives, and executive briefings to align stakeholders.
- Track, report, and optimize key success metrics (cost savings, accuracy, customer satisfaction, retention)."

Other Requirements

Agentic AI consultant

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📌 Senior Technical Lead (India)
🏢 HCLTech
📍 India