We are seeking a highly skilled and passionate AI Engineer to design and build enterprise-grade, production-ready conversational and agentic AI systems that enhance how users interact with enterprise products, services, insights, and recommendations.
This role goes beyond traditional chatbots. You will architect and deliver multi-agent, tool-augmented GenAI solutions capable of reasoning, planning, contextual retrieval, and action execution across multiple enterprise data sources and platforms. You will work on secure, scalable, and governed GenAI systems, aligned with enterprise architecture and compliance standards, ensuring reliability, explainability, observability, and continuous improvement in real-world production environments
Skills:
� Strong understanding of LLMs, transformers, embeddings, prompt engineering, and evaluation techniques.
� Experience building end-to-end GenAI/Agentic AI products, including backend services and frontend web apps.
� Hands-on experience with LangChain, LangGraph, n8n, Co-pilot for building modular, agent-based systems.
� Practical experience designing multi-agent architectures and orchestrating reasoning and action workflows.
� Strong experience with Vector Databases and Graph Databases (Azure AI Search, Neo4j, Databricks Vector DB) for hybrid, semantic and relationship-driven search.
� Proven experience implementing RAG pipelines with structured and unstructured enterprise data.
� Proficiency in Python, SQL, Spark, and familiarity with additional languages (e.g., JavaScript).
� Hands-on experience with PyTorch and TensorFlow.
� Experience working with high-performance, large-scale ML systems in production environments
� Ability to solve complex problems in language understanding, reasoning, and GenAI system design
� Experience deploying GenAI solutions on Azure, including:
o Azure Data Factory (ADF)
o Databricks
o Azure AI Search
o Databricks Genie
o AI Document Intelligence
o App Services, Azure Functions, Bot Framework
o Azure Cache for Redis