We're hiring an AI Solutions Architect who operates at the intersection of applied AI, enterprise data engineering, and cloud-native .NET development. This isn't an advisory role — you'll own architecture decisions end to end, from Databricks lakehouse design through to production LLM and agentic AI systems built on .NET and Azure. You'll work closely with executive stakeholders, engineering squads, and data science teams to shape how intelligent systems are built and scaled across the organization.

What you'll do

• Define and own the enterprise AI architecture strategy — spanning data pipelines, model lifecycle, and intelligent application delivery across Azure.
• Design and govern production Databricks lakehouse platforms: Medallion architecture (bronze/silver/gold), Delta Lake, Unity Catalog governance, and MLflow-based model lifecycle management.
• Architect and deliver end-to-end AI/ML solutions on the .NET ecosystem, integrating Azure OpenAI, Semantic Kernel, and Azure AI Studio into scalable enterprise applications.
• Build feature engineering pipelines on Databricks that feed production ML models and LLM-grounded retrieval systems.
• Lead design of RAG pipelines, vector stores, embedding strategies, and agentic workflows — bridging the data platform to the application layer.
• Lead technical design sessions, set architecture standards, and drive AI governance — reliability, security, observability, and responsible AI practices.
• Translate complex business problems into AI architectures; communicate trade-offs and roadmap decisions to executive and non-technical stakeholders.
• Mentor senior engineers across squads and provide hands-on technical leadership through delivery — not just design.
• Stay current on emerging LLM capabilities and proactively surface adoption opportunities aligned to business outcomes.

What you bring

8–10 years of hands-on software engineering and architecture experience — with genuine ownership of production systems, not advisory or oversight roles.

At least 3 years in a solutions or enterprise architect role, with a track record of driving technology decisions at the director or VP level.

Strong command of C# / .NET (Core / .NET 6/7/8) and cloud-native Azure patterns — microservices, event-driven design, API-first architecture, AKS deployments.

Production-grade Databricks experience: Delta Lake, PySpark/SQL, Databricks Workflows, Medallion architecture, Unity Catalog, and MLflow on Databricks.

Hands-on experience designing and deploying AI/ML systems in production — LLMs, RAG, embeddings, fine-tuning, or agentic architectures.

Proficiency with Azure OpenAI Service, Semantic Kernel, Azure AI Studio, and vector databases (Azure AI Search, Pinecone, or Qdrant).

Deep familiarity with distributed systems, event-driven design (Service Bus, Kafka, Event Grid), and enterprise API patterns (REST, gRPC).

Excellent communication skills — able to write ADRs, run design sessions, and present architecture trade-offs to executives and engineers alike.

Nice to have

• Experience with Databricks Model Serving endpoints or Feature Store integration with real-time inference pipelines.
• Background in regulated industries — fintech, healthcare, insurance, or legal — with compliance framework experience (SOC 2, HIPAA, PCI-DSS).
• MLOps tooling beyond MLflow: Azure ML pipelines, Kubeflow, or Databricks AutoML.
• Contributions to open-source AI, data engineering, or .NET ecosystem projects.
• Experience with multi-cloud architectures spanning Azure and AWS or GCP.

Tech stack

Backend / App

.NET 8 / C#, ASP.NET Core, REST, gRPC, Azure Service Bus, Event Grid

AI / LLM

Azure OpenAI, Semantic Kernel, Azure AI Studio, LangChain, RAG, Agentic AI

Data platform

Databricks, Delta Lake, MLflow, Unity Catalog, Databricks Workflows, PySpark

Cloud & infra

Azure Kubernetes Service, Azure Data Factory, Azure Monitor, Terraform, GitHub Actions

Vector & search

Azure AI Search, Pinecone, Qdrant, FAISS, pgvector

Databases

SQL Server, Azure Cosmos DB, PostgreSQL, MongoDB

Why this role stands out

Most AI architect roles live in one world — either the data platform or the application layer. This role owns both. You'll design the Databricks pipelines that govern and prepare data, and architect the .NET AI systems that consume and act on it. If you're energized by closing the gap between enterprise data engineering and production AI delivery — and want to do it in one of the most architecturally rich tech markets in the US — this role was built for you.

Hard requirements — please read before applying

Location: This role is based in Chicago, IL. Candidates must be able to work on-site or in a hybrid capacity in the Chicago area. Remote-only applicants will not be considered.

Work Mode : Contract