AI Developer

6 days ago

Hyderabad Jubilee Ho Hyderabad Telangana, India be815906-17b8-4f09-8d82-5854fdf73f0b Full time ₹ 2,00,000 - ₹ 3,50,000 per year

About the Role

Hiring an AI Engineer with deep practical experience in working with LLMs, RAG pipelines, knowledge graphs, agents, and automation workflows.

You will build production-grade AI systems that can autonomously retrieve information, process documents, trigger actions, and integrate with external tools/APIs.

Must be able to work collaboratively during U.S. Central Time (CST) hours.

This role is ideal for someone who understands both AI architecture and software engineering, and can take a problem from concept → prototype → production.

Key Responsibilities LLM Engineering & Architecture

  • Design, develop, and optimize RAG systems (vector storage, chunking, retrieval tuning, hybrid search).
  • Implement Graph-RAG, knowledge-graph creation, entity + relationship extraction.
  • Build and fine-tune LLMs (LoRA, QLoRA, instruction tuning).
  • Evaluate LLM responses using metrics like RAGAS, precision/recall, and custom evaluation frameworks.
  • Build multi-step AI agents using LangChain, LangGraph, or custom frameworks.
  • Create task automation pipelines (email automation, marketing automation, workflow orchestration).
  • Integrate tools such as DuckDuckGo Search, Browser automation, custom Python tools, and API connectors.
  • Implement error handling, retries, monitoring, logging, and chain debugging.
  • Design FastAPI or Django-based backends for AI services.
  • Create REST APIs to expose LLM workflows to frontend or other services.
  • Deploy models on cloud GPU providers (AWS, GCP, Nebius, TensorDock, etc.).
  • Build scalable data pipelines for document ingestion, cleaning, and extraction.
  • Work with embeddings, chunking strategies, token optimization, and retrieval performance tuning.
  • Manage vector DBs: FAISS / Chroma / Pinecone / Weaviate, etc.
  • Deploy and scale LLMs using vLLM, Hugging Face TGI, or custom inference servers.
  • Set up Docker, CI/CD, versioning, logging, and monitoring pipelines.
  • Strong understanding of transformers, embeddings, tokenization.
  • Experience with LangChain, LangGraph, LlamaIndex, or custom agent frameworks.
  • Hands-on with RAG, Graph-RAG, chunking, hybrid search, metadata-based retrieval.
  • Ability to evaluate and debug LLM hallucinations + retrieval gaps.
  • Python (mandatory)
  • FastAPI, Flask, or Django
  • Docker, Git, CI/CD
  • Cloud deployment: AWS/GCP/Azure, or GPU clouds
  • Vector DB experience (FAISS, Pinecone, Chroma, Weaviate)

Good to Have

  • Experience in knowledge-graph or Neo4j
  • Experience in automation tools (Zapier, n8n, Make)
  • Experience in email automation or marketing workflows
  • UI knowledge ) is a bonus
  • Experience with multi-agent systems / autonomous agents

What We're Looking For

  • Someone who can build end-to-end AI systems, not just chatbots.
  • Someone who understands production scaling, not just notebooks.
  • Someone who can think in terms of agents, graph-based retrieval, automation flows.
  • Someone who stays updated on LLM architectures, inference optimizationss.

Job Types: Full-time, Permanent

Pay: ₹20, ₹35,000.00 per month

Expected Start Date: 01/12/2025

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