Senior GenAI Engineer

We are seeking an experienced Senior GenAI Engineer with LangGraph / LangChain, MLflow to design, build, and deploy enterprise-scale Generative AI solutions leveraging LLMs, RAG architectures, and modern data platforms. The ideal candidate should possess strong expertise in LangChain, LangGraph, MLflow, Databricks, PySpark, and production-grade AI deployment frameworks. The role involves building scalable AI applications, developing intelligent agents, optimizing retrieval systems, and collaborating with data engineering and product teams to deliver impactful AI solutions. Technical Requirements: AI Platform Engineering Build scalable AI platforms on Databricks and cloud environments. Develop model lifecycle management solutions using MLflow. Implement model tracking, versioning, deployment, monitoring, and governance. Support MLOps and LLMOps initiatives. Data Engineering Build and optimize large-scale data pipelines using PySpark. Process structured and unstructured data for AI and analytics workloads. Collaborate with data engineering teams to build feature and knowledge pipelines. Ensure data quality, lineage, and governance standards. Responsibilities: Generative AI Development Design and implement enterprise GenAI applications using LLMs. Develop multi-agent workflows and agentic AI systems using LangGraph. Build conversational AI, copilots, knowledge assistants, and intelligent automation solutions. Engineer prompts and workflows to optimize model performance and user experience. RAG & Knowledge Systems Design and implement Retrieval-Augmented Generation (RAG) pipelines. Integrate vector databases and document retrieval frameworks. Optimize document chunking, embeddings, indexing, retrieval, and reranking strategies. Improve response accuracy, latency, and relevance of AI systems. Preferred Skills: Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)