We are seeking an AI & Microsoft Fabric Engineer to design and develop enterprise AI solutions using Agentic AI, Generative AI, Azure OpenAI, RAG, and Microsoft Fabric. The role focuses on building AI agents, semantic data solutions, and scalable data pipelines to automate workflows and enable intelligent data-driven decisions.
Required Skills
- Strong experience with Agentic AI, including AI agents, reasoning, planning, memory, tool/function calling, multi-agent orchestration, guardrails, and evaluation.
- Hands-on experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar AI orchestration frameworks.
- Expertise in LLM/GenAI solutions including Azure OpenAI/OpenAI, RAG, embeddings, vector search, hybrid search, prompt engineering, grounding, and hallucination mitigation.
- Strong Microsoft Fabric experience with:
- Lakehouse, Warehouse, OneLake
- Data Factory, Dataflows, Notebooks
- Power BI semantic models, Direct Lake, Delta Lake
- Medallion architecture
- Experience with ontology and semantic modeling, including entities, relationships, taxonomy, metadata, lineage, semantic layers, knowledge graphs, RDF/OWL/SPARQL, or graph databases.
- Strong programming skills in Python, SQL, Spark/PySpark, REST APIs, Git, CI/CD, monitoring, logging, and cloud security.
Roles & Responsibilities
- Design and implement enterprise-grade Agentic AI solutions using LLMs, RAG, APIs, and enterprise data sources.
- Integrate AI agents with Microsoft Fabric Lakehouse/Warehouse, semantic models, applications, and document repositories.
- Build and optimize RAG pipelines using embeddings, vector/semantic search, structured data grounding, and evaluation frameworks.
- Develop ontology-driven semantic models supporting business rules, metadata, governance, and data lineage.
- Design and build Fabric data solutions using Data Factory, Notebooks, Spark/PySpark, SQL, Delta Lake, and medallion architecture.
- Implement AI governance practices including guardrails, access controls, monitoring, logging, security, and cost optimization.
- Create technical designs, architecture diagrams, reusable components, and development standards.
- Collaborate with business and technical teams to translate business processes into semantic data products and AI workflows.
Preferred Qualifications
- Experience delivering production-grade GenAI and AI automation solutions.
- Strong Azure cloud experience and enterprise data platform knowledge.
- Experience with Agile development and production support.