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Forward Deployed Engineer - Agentic AI

Forward Deployed Engineer - Agentic AI

Undisclosed
3-8 Years
Not Disclosed
Early Applicant
  • Posted 3 days ago
  • Be among the first 10 applicants

Job Description

Forward Deployed Engineer – Agentic AI

Location: Gurugram, India – On-site

Experience: 3- 8 years

About the Role

We are looking for a Forward Deployed Engineer – Agentic AI to build and deploy LLM-powered agentic solutions for real-world business use cases. The role involves close collaboration with business and technical stakeholders.

Job Responsibilities

  • Design, develop and deploy LLM-powered agents using LangChain, LangGraph and Google ADK.
  • Build agent workflows involving tool/function calling, RAG, multi-step reasoning and state management.
  • Integrate agents with APIs, databases and third-party systems using MCP (Model Context Protocol) and custom tools.
  • Collaborate with stakeholders to understand requirements, develop prototypes and implement solutions.
  • Develop evaluations and guardrails to improve agent accuracy and reliability.
  • Debug production agents, analyse logs and resolve reliability issues.
  • Use AI coding tools such as Claude Code, Cursor and GitHub Copilot in the development workflow.

Required Skills

  • B.Tech/B.E./M.Tech/MCA in CS, IT or related field.
  • 2–3 years of experience with strong Python skills.
  • Hands-on experience with LLM/GenAI projects.
  • Experience with at least two of: LangChain, LangGraph, Google ADK, LlamaIndex, CrewAI or similar agent frameworks.
  • Strong understanding of RAG, prompting, tool/function calling, embeddings and vector stores.
  • Good knowledge of Git, REST APIs and basic SQL.
  • Good communication and stakeholder management skills.

Good to Have

  • FastAPI/Flask, Docker and cloud exposure (AWS/GCP/Azure).
  • MCP, agent-to-agent orchestration.
  • LLM evaluation/benchmarking.
  • LangSmith/Langfuse or similar observability tools.

Interested candidates can apply at: [Confidential Information]

Key Skills

embeddings

Claude

RAG prompting

LangSmith

LangGraph

LLM evaluation benchmarking

MCP agent-to-agent orchestration

Langfuse

LangChain

CrewAI

tool function calling

LLM GenAI projects

vector stores

GitHub Copilot

MCP Model Context Protocol

Google ADK

LlamaIndex

Cursor

About Company

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