10 Aug
|
Leading
|
Hyderabad
Job Title
Senior Generative AI Developer
Experience
- 5–8 Years of overall software development experience
- 3+ Years of hands -on experience in Generative AI / LLM application development
Role Overview
We are seeking a highly skilled Senior Generative AI Developer to design, develop, and deploy enterprise -grade Generative AI applications using Large Language Models (LLMs), Retrieval -Augmented Generation (RAG), and Agentic AI frameworks. The ideal candidate should have strong expertise in Python, AI orchestration frameworks, cloud platforms, and up-to-date AI application architecture. You will work closely with AI Architects, Data Scientists, Product Managers, and Full Stack Engineers to build scalable AI -powered solutions.
Requirements
Key Responsibilities
Generative AI Application Development
- Design and develop production -grade GenAI applications using LLMs, RAG, and Agentic AI.
- Build conversational AI assistants, enterprise chatbots, document intelligence platforms, and AI copilots.
- Develop AI -powered workflows using LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI,
or Google ADK.
- Integrate OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, or AWS Bedrock models.
RAG & Knowledge Management
- Design Retrieval -Augmented Generation (RAG) pipelines.
- Implement document ingestion, chunking, embedding generation, semantic search, and retrieval.
- Build vector search solutions using Pinecone, FAISS, ChromaDB, Weaviate, pgvector, Qdrant, or Azure AI Search.
- Optimize retrieval quality using hybrid search, reranking, and prompt engineering.
Agentic AI Development
- Develop autonomous AI agents and multi -agent workflows.
- Build tool -calling agents and workflow orchestration.
- Implement Model Context Protocol (MCP) integrations.
- Design memory management and agent planning strategies.
Backend & API Development
- Develop scalable backend services using Python and FastAPI.
- Build REST APIs and microservices for AI applications.
- Integrate enterprise systems and third -party APIs.
- Ensure secure, scalable, and high -performance AI services.
Cloud & MLOps
- Deploy AI applications on Azure, AWS, or GCP.
- Containerize applications using Docker and Kubernetes.
- Implement CI/CD pipelines for AI deployments.
- Monitor LLM performance, latency, hallucinations, and production health.
Collaboration
- Work closely with AI Architects and Product Owners.
- Participate in Agile ceremonies.
- Mentor junior AI engineers.
- Contribute to architecture discussions and code reviews.
Required Skills & Qualifications
Experience
- 5–8 years of software development experience.
- 3+ years of hands -on experience in Generative AI.
- Experience building production AI applications.