AI Applied Architect (.NET & Databricks)

We're looking for a seasoned AI Applied Architect with deep .NET expertise and hands-on Databricks experience to lead the design and delivery of enterprise-grade AI and data intelligence systems. You'll sit at the intersection of software architecture, applied AI, and modern data engineering - shaping how we build, scale, and govern intelligent applications across our product portfolio. This is a high-impact role with visibility at the executive level and meaningful influence over our long-term technology roadmap., * Architect and deliver end-to-end AI/ML solutions on the .NET ecosystem, including integration with Azure AI, OpenAI, and Semantic Kernel.

• Design and own enterprise-scale Databricks lakehouse architectures - including Medallion (bronze/silver/gold) pipelines, Delta Lake, Unity Catalog governance, and MLflow-based model lifecycle management.
• Lead technical design sessions, define architecture standards, and drive decision-making for AI-powered product features.
• Collaborate with product managers, data scientists, and engineering teams to translate business requirements into scalable AI and data architectures.
• Evaluate and recommend frameworks, tools, and cloud services for AI workloads - model serving, RAG pipelines, vector stores, agents, and feature engineering on Databricks.
• Build and govern feature engineering pipelines on Databricks, feeding production ML models and LLM-grounded retrieval systems.
• Establish and enforce best practices for AI system reliability, security, observability, and responsible AI governance.
• Mentor senior engineers and provide technical leadership across multiple squads.
• Stay current on emerging AI/LLM capabilities and proactively identify opportunities for adoption., Backend .NET 8 / C#, ASP.NET Core, gRPC, REST APIs AI / LLM Azure OpenAI, Semantic Kernel, Azure AI Studio Data Platform Databricks (Delta Lake, MLflow, Unity Catalog, Workflows) Cloud & Infra Azure Kubernetes Service, Azure Data Factory, Azure Service Bus Vector & Search Azure AI Search, Pinecone, Qdrant, FAISS Databases SQL Server, Azure Cosmos DB, PostgreSQL DevOps GitHub Actions CI/CD, Docker, Kubernetes, Terraform Observability Azure Monitor, Prometheus, Grafana, MLflow tracking

Do you have experience in Web services design?, * 8+ years of software engineering experience, with at least 3 years in a solutions or enterprise architect role.

• Strong command of C# / .NET (Core / .NET 6/7/8) and cloud-native patterns on Azure.
• Hands-on experience designing and deploying AI/ML systems in production - LLMs, RAG, embeddings, fine-tuning, or agentic architectures.
• Proficiency with Azure OpenAI Service, Azure AI Studio, Semantic Kernel, and/or LangChain equivalents in .NET.
• Production-grade Databricks experience: Delta Lake, PySpark/SQL, Databricks Workflows, Medallion architecture, Unity Catalog, and MLflow on Databricks.
• Deep familiarity with microservices, event-driven design, API design, and distributed systems.
• Proven track record leading cross-functional teams and driving large-scale technology initiatives.
• Excellent communication skills - able to translate complex technical concepts for executive and non-technical audiences.

Nice to have

• Experience with MLOps tooling beyond MLflow: Azure ML, Kubeflow, or Databricks Model Serving endpoints.
• Familiarity with vector databases (Pinecone, Qdrant, Azure AI Search).
• Background in regulated industries (fintech, healthcare, legal).
• Experience integrating Databricks Feature Store with real-time inference pipelines.
• Contributions to open-source AI/ML or data engineering projects.

Tech stack