Gen AI Developer (Exp-7 Y)-Hybrid-Full time

We are looking for an experienced GenAI Developer with strong expertise in Python, Generative AI, and Large Language Models (LLMs). The ideal candidate will be responsible for designing, developing, and deploying AI-powered applications, RAG-based solutions, and intelligent automation workflows.

Key Responsibilities

• Design, develop, and implement Generative AI applications using Python and modern AI frameworks.

• Build and integrate LLM-powered solutions using OpenAI, Azure OpenAI, Anthropic, or similar platforms.

• Develop Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge management and intelligent search.

• Implement AI workflows and applications using LangChain and LangGraph.

• Work with vector databases for embedding generation, semantic search, and information retrieval.

• Develop prompt engineering strategies to improve LLM accuracy, relevance, and response quality.

• Integrate AI models with REST APIs, databases, and enterprise applications.

• Build scalable backend services using Python frameworks such as FastAPI or Flask.

• Implement AI model evaluation, monitoring, security, and performance optimization.

• Collaborate with data scientists, architects, and engineering teams to deliver production-ready AI solutions.

Required Skills

• 7+ years of experience in software development, with strong Python programming skills.

• Hands-on experience in Generative AI and Large Language Models (LLMs).

• Strong knowledge of OpenAI, Azure OpenAI, or other LLM platforms.

• Experience developing RAG-based applications and AI-powered solutions.

• Hands-on experience with LangChain, LangGraph, or similar AI frameworks.

• Knowledge of prompt engineering, embeddings, and semantic search.

• Experience with vector databases such as Pinecone, FAISS, Chroma, or Weaviate.

• Strong experience with REST APIs, FastAPI/Flask, and backend development.

• Knowledge of SQL/NoSQL databases, Git, Docker, and CI/CD pipelines.

• Understanding of cloud platforms such as AWS, Azure, or Google Cloud Platform.

Good to Have

• Experience with Agentic AI, AI agents, and multi-agent workflows.

• Knowledge of MCP (Model Context Protocol) and tool/function calling.

• Experience with AWS Bedrock or Azure AI Foundry.

• Familiarity with Kubernetes, microservices, and cloud deployments.

• Experience with LLM evaluation, guardrails, and responsible AI practices.