GenAI Lead

We are seeking a highly skilled AI Engineer with 10+ years of experience to design, develop, and deploy production-ready. AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. The ideal candidate will have hands-on experience building enterprise-grade AI applications, integrating them with business systems, and driving AI adoption through scalable, secure, and governed solutions. The initial engagement will focus on understanding business problems, translating them into AI solution architectures, and developing an intelligent RAG and Agentic AI layer that addresses the identified use cases. As the AI program matures, the role will expand to building robust production-grade AI platforms and intelligent automation capabilities. Key Responsibilities AI Solution Design & Development Partner with business stakeholders to understand complex business challenges and identify opportunities for AI-driven transformation. Translate business requirements into scalable AI solution architectures. Design and develop production-ready AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. Build intelligent workflows capable of reasoning, planning, and executing multi-step business processes using AI agents. RAG & Knowledge Systems Design and implement Retrieval-Augmented Generation (RAG) architectures. Develop document ingestion, indexing, embedding, and retrieval pipelines. Build enterprise knowledge assistants capable of answering domain-specific questions with high accuracy and traceability. Optimize retrieval quality using vector databases, hybrid search, metadata filtering, and reranking techniques. LLM Engineering Develop AI services using leading foundation models (OpenAI GPT, Anthropic Claude, Gemini, Llama, Mistral, etc.). Implement prompt engineering, prompt chaining, function calling, structured outputs, and model orchestration. Fine-tune and optimize AI applications for accuracy, latency, scalability, and cost efficiency. Agentic AI Development Build autonomous and semi-autonomous AI agents capable of interacting with enterprise systems. Design multi-agent workflows for complex business scenarios. Integrate AI agents with APIs, databases, enterprise applications, and workflow orchestration platforms. Engineering & Integration Develop REST APIs and microservices to expose AI capabilities. Integrate AI applications with enterprise platforms, data warehouses, and business systems. Build scalable deployment pipelines using cloud-native architectures. Collaborate closely with Data Engineering, Platform Engineering, and Application Development teams. AI Governance & Operations Implement AI observability, monitoring, evaluation, and performance measurement. Ensure responsible AI practices, governance, security, and compliance. Monitor model quality, hallucinations, prompt effectiveness, and operational metrics. Drive continuous improvements in AI reliability and user experience. Required Skills Technical Skills Strong proficiency in Python.Experience with Generative AI frameworks such as LangChain, LlamaIndex,LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.Hands-on experience with Retrieval-Augmented Generation (RAG) architectures.Experience working with Large Language Models (OpenAI, Claude, Gemini, Llama,Mistral, etc.).Familiarity with vector databases such as Pinecone, Milvus, Weaviate, Chroma, orFAISS.Experience developing REST APIs using FastAPI, Flask, or similar frameworks.Knowledge of cloud platforms (AWS, Azure, or GCP).Experience with Docker, Kubernetes, CI/CD, and modern software engineeringpractices.AI & Data SkillsPrompt engineering and prompt optimization.Embedding models and semantic search.Agent orchestration and tool integration.AI evaluation frameworks.Knowledge graph integration (preferred).Experience with structured and unstructured enterprise data. We are seeking a highly skilled AI Engineer with 10+ years of experience to design, develop, and deploy production-ready. AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks. The ideal candidate will have hands-on experience building enterprise-grade AI applications, integrating them with business systems, and driving AI adoption through scalable, secure, and governed solutions. The initial engagement will focus on understanding business problems, translating them into AI solution architectures, and developing an intelligent RAG and Agentic AI layer that addresses the identified use cases. As the AI program matures, the role will expand to building robust production-grade AI platforms and intelligent automation capabilities. Key Responsibilities AI Solution Design & Development Partner with business stakeholders to understand complex business challenges