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Walking Tree
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Gen AI Engineer

Gen AI Engineer

Walking Tree

3 - 8 years

5 - 8 Lacs

Hyderabad

Posted:3 days ago| Platform:

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Skills Required

continuous integration cd kubernetes python project management microsoft azure ci/cd engineering cloud deployment artificial intelligence docker ansible react.js git gcp devops mule esb linux jenkins aws cloud computing programming architecture

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Skills:

Job Type:

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Exp Level:

Job Summary

We are seeking a passionate and skilled Generative AI Engineer with 3+ 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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