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UsefulBI Corporation · Pune District, Maharashtra, India

Gen AI Developer

Hybridseniorfull timePosted yesterday
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Stack mentioned

agentic-aillmragopenaigeminipythonlangchainllamaindexpineconeweaviatenlpfastapiawsazuregcpci/cddockergenerative-aiprompt-engineeringvector-databases

Location: Bangalore / Lucknow / Pune

Work Model- Hybrid

Role Type: Full-time, Senior Level

Experience: 4-6+ Years

Role Overview

We are looking for a Generative AI / Agentic AI Developer with strong experience in Large Language Models (LLMs), AI Agents, RAG architectures, and intelligent automation systems. The role involves designing, developing, and deploying next-generation AI-powered applications using modern GenAI frameworks and multi-agent architectures. The ideal candidate should have hands-on experience with LLM ecosystems, prompt engineering, AI orchestration frameworks, vector databases, and cloud-based AI deployments. The candidate will work closely with Data Engineering, Product, and AI teams to build scalable AI-driven solutions for enterprise use cases.

Key Responsibilities:

• Design and develop GenAI and Agentic AI applications using LLMs

• Build AI agents, multi-agent workflows, and autonomous task execution systems

• Develop RAG-based pipelines using vector databases and retrieval frameworks

• Integrate LLMs such as OpenAI, Claude, Gemini, Llama, or Mistral into enterprise applications

• Work on prompt engineering, fine-tuning, evaluation, and response optimization

• Build AI-powered assistants, Q&A systems, summarizers, automation bots, and intelligent workflows

• Develop scalable APIs and backend services for AI applications

• Collaborate with Data Engineering and Product teams for AI solution deployment

• Optimize model performance, latency, and cost efficiency

Required Skills:

• Strong proficiency in Python

• Hands-on experience with LLMs and Generative AI frameworks

• Experience with LangChain, LangGraph, CrewAI, LlamaIndex, or similar frameworks

• Strong understanding of RAG architecture and vector databases (Pinecone, ChromaDB, FAISS, Weaviate, etc.)

• Experience with prompt engineering and LLM optimization

• Exposure to multi-agent systems and Agentic AI workflows

• Knowledge of NLP, embeddings, semantic search, and AI orchestration

• Experience with REST APIs, FastAPI, or backend integration

• Exposure to cloud platforms such as AWS, Azure, or GCP

• Understanding of CI/CD, Docker, and deployment workflows

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