Live opening · Posted 19 days ago

Gen AI Developer

UsefulBI Corporation · Pune District, Maharashtra, India (Hybrid)
Linkedin No
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At a glance

The key details from the original listing.

Posted 19 days ago
CompanyUsefulBI Corporation
LocationPune District, Maharashtra, India (Hybrid)
Work modeNo
SourceLinkedin
Listed19 days ago

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About the role

Description supplied by the original job listing.

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

Work arrangement
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