Python Generative AI Engineer

Themesoft Inc; Chennai; Presencial; INR 1 800 000 - 3 000 000; Tempo integral

Resumo da oferta

Themesoft Inc in Chennai is seeking a Python Generative AI Engineer with deep expertise in LLMs, LangChain, LangGraph, and vector databases to build enterprise-gen AI apps.

The role involves designing, developing, deploying AI agents and RAG-based solutions, integrating REST APIs, and leveraging cloud platforms. Strong Python skills and knowledge of embeddings, NLP, and MLOps are essential.

Qualificações

• Proficient in Python and Gen AI concepts.
• Hands-on experience with LLMs (OpenAI, Azure OpenAI, etc.).
• Experience with LangChain and LangGraph.
• Familiarity with vector databases and embedding-based search.
• Understanding of ML/NLP concepts and data preprocessing.

Responsabilidades

• Design, develop, and deploy enterprise Gen AI applications.
• Build AI agents and intelligent automation workflows.
• Implement RAG-based solutions and retrieval strategies.
• Integrate AI models with REST APIs and cloud services.

Conhecimentos

Python

Generative AI

Large Language Models

Prompt Engineering

RAG

NLP concepts

Embeddings

Machine Learning basics

Cloud technologies

Ferramentas

LangChain

LangGraph

Pinecone

ChromaDB

FAISS

Weaviate

Milvus

FastAPI

Flask

Django

Descrição da oferta de emprego

Job Summary

• We are seeking a skilled Python Generative AI Engineer with expertise in LLMs, LangChain, LangGraph, Vector Databases, and Retrieval-Augmented Generation (RAG) solutions.
• The ideal candidate will be responsible for designing, developing, and deploying enterprise-grade Gen AI applications, AI agents, and intelligent automation solutions leveraging modern AI frameworks and cloud technologies.

Programming AI Technologies

• Strong proficiency in Python.
• Hands-on experience with Generative AI and Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, Llama, etc.).
• Experience with LangChain Framework.
• Experience with LangGraph for building AI agents and workflows.
• Strong understanding of Prompt Engineering techniques.
• Experience in developing RAG-based applications.
• Experience with Vector Databases such as:
• Pinecone
• ChromaDB
• FAISS
• Weaviate
• Milvus
• Knowledge of embeddings and semantic search concepts.
• Experience in document ingestion, chunking, indexing, and retrieval strategies.
• Understanding of Machine Learning and NLP concepts.
• Experience with embeddings, transformers, and LLM architectures.
• Knowledge of data preprocessing and feature engineering.
• Experience working with structured and unstructured datasets.

APIs Integration

• Experience with REST APIs and API integrations.
• Knowledge of FastAPI, Flask, or Django frameworks.
• Experience integrating AI models with enterprise applications and databases.
• Experience with Azure, AWS, or GCP cloud platforms.
• Understanding of Docker and containerization.
• Experience with CI/CD pipelines and deployment automation.
• Knowledge of MLOps concepts and model monitoring.