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Python Generative AI Developer

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Onsite

Python Generative AI Developer

Walking Tree

Python Generative AI Developer

Skills

Google Cloud PlatformDockerReactPythonMachine LearningAIAWSFastAPIAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Chennai, Tamil Nadu, India

Work mode:

Onsite

Published on:

23 September 2026

What they need


Total Exp - 7+ Years

Location - Bangalore

Work Mode - Work from office

Mandatory skills - Python, AI, ML,GenAI,Agentic AI,LLM

Desired skills - Python, AI, ML,GenAI,Agentic AI,LLM

Domain (Industry) - Financial and Wealth management

Job Summary

We are seeking a passionate and skilled Generative AI Engineer with 7+ years of experience in building LLM-based applications. The ideal candidate should have hands-on experience with multi-agent frameworks (LangGraph, CrewAI), agent orchestration, RAG pipelines, and Chain of Thought (CoT) reasoning to develop intelligent, context-aware systems.

Key Responsibilities

  • Design and develop multi-agent LLM applications using frameworks like LangGraph and CrewAI.
  • Build, configure, and orchestrate intelligent agents and tools for autonomous task execution.
  • Implement RAG (Retrieval-Augmented Generation) and Agentic RAG pipelines to augment LLMs with external data sources.
  • Develop and fine-tune prompts to support Chain of Thought and step-wise reasoning.
  • Integrate vector databases (e.g., FAISS, Pinecone, Chroma) for context retrieval.
  • Collaborate with frontend/backend teams to embed GenAI capabilities into products.

Required Skills

  • Strong programming experience with Python.
  • Hands-on with LangGraph, CrewAI, LangChain, or other agent frameworks.
  • Solid understanding of LLMs, prompt engineering, and tool invocation patterns.
  • Experience with RAG, vector databases, embeddings, and document chunking.
  • Knowledge of Chain of Thought prompting, memory handling, and agent planning logic.
  • Familiarity with OpenAI, Hugging Face, or other LLM APIs.

Nice to Have

  • Experience deploying GenAI apps with FastAPI, Streamlit, or React.js.
  • Understanding of semantic search, knowledge graphs, or graph databases.
  • Exposure to MLOps, Docker, CI/CD pipelines, and cloud deployment (AWS/GCP/Azure).

Awareness of ethical AI and data governance practices.

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