AI Applied Architect (.NET)

About the role

We're looking for a seasoned AI Applied Architect with deep .NET expertise to lead the design and delivery of enterprise-grade AI systems. You'll sit at the intersection of software architecture and applied AI — 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.

What you'll do

Architect and deliver end-to-end AI/ML solutions on the .NET ecosystem, including integration with Azure AI, OpenAI, and Semantic Kernel.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 architectures.Evaluate and recommend frameworks, tools, and cloud services for AI workloads (model serving, RAG pipelines, vector stores, agents).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.

What you bring

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.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 (Azure ML, MLflow, Kubeflow).Familiarity with vector databases (Pinecone, Qdrant, Azure AI Search).Background in regulated industries (fintech, healthcare, legal).Contributions to open-source AI/ML projects.

Tech stack

.NET 8 / C#

Azure OpenAI

Semantic Kernel

Azure AI Studio

Azure Kubernetes Service

SQL / CosmosDB

Vector DBs

CI/CD (GitHub Actions)

REST / gRPC APIs