About the Role
Location- Bangalore Chennai and Hyderabad
TE- 5 Years and above
NP- Immediate-15 days
Key Responsibilities
Design and develop LLM-based agents and multi-agent workflows for enterprise use cases
Build and optimize RAG pipelines, including data preparation, embedding strategies, vector search, and retrieval logic
Define agent reasoning patterns, tool usage, memory, and orchestration strategies
Lead experimentation with prompt engineering, chain-of-thought alternatives, and agent planning approaches
Establish evaluation frameworks for LLM outputs, agent behavior, and system performance
Collaborate with data engineers to define data requirements and pipeline interfaces for AI agents
Contribute to Agent Ops practices, including observability, debugging, reliability, and cost optimization
Mentor mid-level team members and influence technical direction
Nice-to-Have / Preferred Requirements
Strong hands-on experience with LLMs (Open AI, Anthropic, open-so...
TE- 5 Years and above
NP- Immediate-15 days
Key Responsibilities
Design and develop LLM-based agents and multi-agent workflows for enterprise use cases
Build and optimize RAG pipelines, including data preparation, embedding strategies, vector search, and retrieval logic
Define agent reasoning patterns, tool usage, memory, and orchestration strategies
Lead experimentation with prompt engineering, chain-of-thought alternatives, and agent planning approaches
Establish evaluation frameworks for LLM outputs, agent behavior, and system performance
Collaborate with data engineers to define data requirements and pipeline interfaces for AI agents
Contribute to Agent Ops practices, including observability, debugging, reliability, and cost optimization
Mentor mid-level team members and influence technical direction
Nice-to-Have / Preferred Requirements
Strong hands-on experience with LLMs (Open AI, Anthropic, open-so...
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