Agentic Ai Developer

ERM Placement Services; Kolkata District, Hyderabad, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

ERM Placement Services is seeking an Agentic AI Developer to design and implement AI agents across multiple business use cases. The role focuses on building end-to-end RAG pipelines, including document ingestion, embedding and vector retrieval.

You will translate business requirements into scalable AI system architectures, balancing automated and human review components while applying MLOps fundamentals to maintain production quality over time.

Qualifications

• Experience designing AI agents and agentic workflows.
• Proficiency with LangChain/LangGraph or similar orchestration frameworks.
• Knowledge of retrieval augmented generation (RAG) and vector stores.
• Understanding of MLOps concepts like experiment tracking and model versioning.

Responsibilities

• Design and develop AI agents and agentic workflows for real business use cases.
• Build end-to-end RAG pipelines including ingestion, chunking, embedding and retrieval.
• Translate requirements into AI system architectures with automation vs human review.
• Evaluate solutions with retrieval and generation quality metrics and monitor drift.

Skills

LangChain

LangGraph

RAG pipelines

MLOps

Job description

Job Title: Agentic AI Developer

Location: Bangalore, Hyderabad, Kolkata

Core Responsibilities AI Agent Development

• Design and develop AI agents and agentic workflows using orchestration frameworks (LangChain, LangGraph) for real business use cases.
• Build end-to-end RAG pipelines — document ingestion, chunking, embedding, vector retrieval, reranking, and grounded response generation.
• Translate business requirements into clear AI system architectures, specifying automated functions versus those needing human review.
• Evaluate AI solutions using appropriate retrieval and generation quality metrics; build lightweight eval harnesses and monitor for drift or degradation.

Apply MLOps fundamentals — experiment tracking, model versioning, and drift detection — to maintain production AI quality over time