Agentic AI Jobs in India: Roles, Salary, Skills, and Career Opportunities

Key Highlights

• Some of the top Agentic AI jobs in India are Agentic AI Engineer, AI Automation Specialist,  Machine Learning Engineer, and AI Product Manager.
• The demand for Agentic AI jobs in India is on the rise, especially across major technology hubs such as Bengaluru, Noida, Delhi, Gurugram, and Pune.
• As Agentic AI is increasingly being used by businesses to plan tasks, analyse information, and complete multi-step workflows. 
• In this blog, you’ll learn about the top 18 Agentic AI jobs, their salary ranges, the skills employers ask for, the industries that are hiring, and a five-step plan to get your first offer. 

Explore Generative AI and Agentic AI Courses Online by upGrad to develop relevant AI skills and learn how intelligent systems can automate tasks, solve problems, and support business workflows.

Top Agentic AI Job Roles in India

As AI is increasingly being used across every Industry now. The demand for agentic AI is on its peak. 

Here are the roles that appear the most in agentic AI jobs in India right now:

Agentic AI Engineer

Agentic AI Engineers builds agents that can plan, use tools, and finish multi step tasks. This involves use of Python, LangGraph or CrewAI, and a lot of debugging when an agent loops or loses context.

AI Automation Specialist

The AI Automation Specialist is the person who bridges the gap between the agents and the real-world activities performed in the business. The tools used are n8n, Zapier, and Python scripting.

Machine Learning Engineer

The job of a Machine Learning Engineer involves training and tuning of the models. Agentic organizations usually hire an ML engineer to ask him to build agent logic on top of existing pipelines.

AI Product Manager

The role of an AI Product Manager is to determine which tasks the agent should be handling and at what point humans need to be kept in the loop. This person collaborates with various teams such as engineers, designers, business people, and end users.

AI Solutions Architect

An AI Solutions Architect is the one who designs the full system around the agent, from model choice and data storage to cloud cost and security. 

Client facing work is very common in this job role.

AI Governance and Ethics Specialist

An AI Governance and Ethics Specialist is the one who help organisations manage risks associated with AI systems.

This job role demands you to write the rules for what agents may do, reviews risk, and prepares audit trails. Banking and healthcare firms need this role.

AI Agent Developer

An AI Agent Developer codes individual agents and their tools. It's close to the Agentic AI Engineer role, but the scope is narrower, usually one agent or one workflow.

Conversational AI Designer

Conversational AI Designer, is the one who designs the way an agent speaks, asks follow-up questions, and manages the confusion. It involves designing the conversation flow, understanding the user’s intentions, handling the unknown input, and transferring the request to humans.

AI Integration Engineer

The AI Integration Engineer is responsible for integrating the agents with the CRMs, ERPs, and internal databases. They deal with issues such as APIs, authentication, data formatting, error handling and systems testing.

LLM Engineer

An LLM Engineer works directly with large language models. Daily tasks will include prompt design, fine tuning, retrieval pipelines, and cutting token costs.

AI Workflow Engineer

The AI Workflow Engineer translates the business process flow to a set of tasks an agent will undertake. This involves human approval checks along the way.

AI Operations (AIOps) Specialist

The AI Operations (AIOps) Specialist is responsible for managing the agents in production environments. They use the power of AI and machine learning to analyze the IT operational data and detect anomalies.

AI Data Engineer

A AI Data Engineer builds the pipelines and vector databases that feed agents clean, current data. They work with databases, data processing tools, document stores, and vector databases used for retrieval.

AI Safety Engineer

An AI Safety Engineer evaluates agents for prompt injection, data leakages, and harmful actions. It is a job which includes evaluation, access controls, adversarial attacks and safety considerations when using tools.

AI Research Engineer

An AI Research Engineer implements research papers into prototypes. Companies and labs employ such engineers, and having a master’s degree or publications would be beneficial.

AI Implementation Consultant

An AI Implementation Consultant assists client organizations to use the agents. They help collect requirements, find proper use cases, manage teams of developers, and participate in testing.

Multi-Agent Systems Engineer

A Multi-Agent Systems Engineer creates a system where there will be more than one agent involved, like the agent for research, writing and reviewing the work. For example, one agent can collect data, another checks the results and prepares a report.

The problem is in the coordination. Developers manage conflicting outputs, shared information, repeated actions, and the cost of running several agents.

AI Strategy Consultant

An AI Strategy Consultant advises leadership on where agents will pay off and where they won't. Writing a sharp business case counts for more than writing code here.

Want to build expertise in applied AI? Explore the Executive Post Graduate Programme in Applied AI and Agentic AI by upGrad to strengthen your understanding of AI applications, agent-based systems, and practical approaches to solving business challenges.