Gen AI Developer (Exp-5+ Yeras) -Full Time-Onsite-In-Person Interview

Python | Generative AI | LLM | RAG | Prompt Engineering | REST APIs | LangChain | Vector Databases | AWS/Azure/OpenAI

Job Summary

We are looking for an experienced GenAI Developer to design, develop, and deploy enterprise-grade Generative AI and LLM-powered applications. The ideal candidate should have strong Python development experience along with hands-on expertise in LLM integration, RAG, prompt engineering, AI agents, APIs, vector databases, and cloud-based AI services. Current GenAI roles commonly combine Python with RAG, agents, vector search, LLM APIs, and production deployment.

Key Responsibilities

• Design and develop Generative AI / LLM-powered applications for enterprise use cases.
• Integrate foundation models from OpenAI, Azure OpenAI, AWS Bedrock, Anthropic, or Google Gemini.
• Develop RAG (Retrieval-Augmented Generation) pipelines for enterprise knowledge applications.
• Implement document ingestion, chunking, embeddings, retrieval, reranking, and response generation.
• Design and optimize prompt engineering strategies for different business use cases.
• Build AI-powered applications such as:
  • Enterprise chatbots
  • AI assistants / copilots
  • Document summarization
  • Question-answering systems
  • Knowledge assistants
  • Document intelligence
• Develop AI Agents / Agentic AI workflows capable of tool calling and multi-step task execution.
• Integrate LLMs with enterprise applications, databases, REST APIs, and external tools.
• Build backend services and APIs using Python, FastAPI, or Flask.
• Develop reusable components for AI workflows and LLM integrations.
• Implement guardrails, validation, security, and responsible AI practices.
• Evaluate LLM responses for accuracy, hallucinations, consistency, and relevance.
• Optimize AI applications for latency, scalability, reliability, and token/cost efficiency.
• Deploy and support GenAI applications in cloud environments.
• Monitor production AI applications and troubleshoot issues.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, Product Owners, and Architects.

Required Technical Skills

• Strong hands-on experience with Python.
• Strong understanding of Generative AI and Large Language Models (LLMs).
• Experience with Prompt Engineering.
• Hands-on experience building RAG applications.
• Experience with embeddings and semantic search.
• Experience with vector databases such as: