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AI Engineer – GenAI / LLM / Agentic AI (4+years)

The Growth Hive

Pune / Kharadi

4+ years

Today

$6.0K–12.0K/yr

Full time

Onsite

Skills Required LLM

RAG

Agentic AI

Gen AI

LangChain

Embeddings

Vector Database

LangGraph

Semantic Search

Hybrid Search

Reranking

Python

FastAPI

Azure

AWS

Description Seeking a hands-on AI Engineer experienced in building and deploying production-grade Generative AI, LLM, RAG, and Agentic AI solutions.

Role: AI Engineer – GenAI / LLM / Agentic AI

Location: Pune

Experience

- 4+ Years

Responsibilities

- Build and deploy LLM/GenAI applications and AI agents
- Develop RAG pipelines including chunking, embeddings, vector search, hybrid retrieval and reranking
- Design multi-agent workflows using LangChain/LangGraph or similar frameworks
- Develop scalable Python/FastAPI backend services and REST APIs
- Work with Azure/AWS/GCP and Docker/Kubernetes for deployment
- Implement LLM evaluation, monitoring, guardrails and hallucination reduction
- Optimize AI applications for accuracy, latency and cost
- Take end-to-end ownership from development to production deployment





Additional Responsibilities

- Work location is in person

Nice To Have

- Experience with LLM evaluation, observability, tool calling, function calling, multi-agent orchestration and production AI systems

More Skills Semantic/Hybrid Search, GCP, Docker, CI/CD

Prepare for this role

Recommended resources to build the skills for this position. Sponsored.

Top 15 Embeddings Interview Questions (Quick)

Zenaique A shorter embeddings interview prep set for quick review.

Top 50 LangChain Interview Questions

Zenaique

Curated LangChain interview questions covering chains, agents, and memory.

Top 50 RAG Interview Questions

Zenaique

Curated RAG interview questions and answers from Zenaique.

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