Job Description
Job Description
Location: Dallas, TX
Duration: 6-month contract
Experience: 8+ years
Work Authorization: Only U.S. Citizens and Green Card holders will be considered. Candidates must be able to work on our W2.
Position Summary
We are seeking an 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. The role sits at the intersection of software architecture, applied AI, and modern data engineering — architecting .NET AI applications, designing Databricks lakehouse pipelines, and collaborating with product managers, data scientists, and engineering teams to deliver scalable, governed AI solutions.
Technical Stack
- 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
Responsibilities
- Architect and deliver end-to-end AI/ML solutions on the .NET ecosystem, integrating Azure AI, OpenAI, and Semantic Kernel
- Design and own Databricks lakehouse architectures — 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 decisions for AI-powered product features
- Evaluate and recommend frameworks and cloud services for AI workloads — model serving, RAG pipelines, vector stores, agents, and feature engineering on Databricks
- Establish best practices for AI system reliability, security, observability, and responsible AI governance
- Mentor senior engineers and provide technical leadership across multiple squads
Required Experience
- 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
- Production-grade Databricks experience: Delta Lake, PySpark/SQL, Databricks Workflows, Medallion architecture, Unity Catalog, and MLflow
- Deep familiarity with microservices, event-driven design, API design, and distributed systems
- Nice to have: MLOps tooling beyond MLflow (Azure ML, Kubeflow, Databricks Model Serving), vector databases, and background in regulated industries (fintech, healthcare, legal)