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# AI Applied Architect (.NET & Databricks)

- **Company:** SYMHAS L.L.C.
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Unity 3d, ASP.NET, .NET Framework, Artificial Intelligence, Automated Storage and Retrieval Systems, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Cloud Engineering, Data Architecture, Information Engineering, Data Infrastructure, DevOps, Distributed Systems, Github, Data Intelligence, PostgreSQL, Machine Learning, Open Source Technology, Performance Tuning, Software Architecture, Cloud Services, Prometheus, Azure Machine Learning, Search Technologies, Software Engineering, SQL Databases, Web Services, Azure Service Bus, Feature Engineering, Azure Data Factory, Cloud Monitoring, Delivery Pipeline, Large Language Models, Grafana, Backend, Event Driven Architecture, Data Lakes, Pyspark, Kubernetes, Cosmos DB, Azure AKS, Machine Learning Operations, Api Design, Restful APIs, Terraform, Grpc, Docker, Databricks, Microservices
- **Published:** June 6, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c3c1f686434a6c4c

## About the Role

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

## Description

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


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