Senior AI-Enabled .NET Engineer / Solution Architect

About the role

We are seeking a self‑driven senior professional to design and deliver AI‑enabled, secure and scalable enterprise solutions built on the .NET platform. The role blends deep .NET architecture expertise with hands‑on experience in generative AI, large language models and cloud AI services.

Key responsibilities

• Design, develop and operate AI‑enabled enterprise applications using C#.NET and ASP.NET Core.
• Identify and translate business needs into AI use cases, process flows, data models and production‑grade code.
• Build generative AI solutions with large language models, retrieval‑augmented generation, embeddings and agentic workflows.
• Implement AI services on Azure AI Foundry and Google Cloud AI, integrating models securely with APIs, databases and enterprise platforms.
• Design, publish and govern APIs using Azure API Management and Google Cloud Apigee, establishing standards for lifecycle, security and observability.
• Create API gateways for internal, partner, public, mobile, microservice and model endpoints, applying controls such as token quotas and responsible‑AI guardrails.
• Develop microservices, event‑driven systems and data pipelines across Azure, GCP, on‑premises and hybrid environments.
• Work hands‑on with SQL Server, PostgreSQL, Azure Cosmos DB, vector‑search technologies, Docker and Kubernetes.
• Collaborate with product, data, frontend, mobile, security and operations teams, taking end‑to‑end ownership from discovery to production.

Required profile

• Proven senior‑level experience in .NET architecture and enterprise solution design.
• Practical knowledge of generative AI, large language models and AI agents.
• Ability to spot valuable AI use cases and integrate them into scalable applications.
• Strong collaboration skills across cross‑functional teams and end‑to‑end delivery mindset.

Required skills

• C#
• .NET
• ASP.NET Core
• Azure AI Foundry
• Google Cloud AI
• Azure API Management
• Google Cloud Apigee
• Large language models
• Generative AI
• RAG (retrieval‑augmented generation)
• Embeddings & vector search
• AI agents & tool calling
• SQL Server
• PostgreSQL
• Azure Cosmos DB
• Vector‑search technologies
• Docker
• Kubernetes
• Microservices
• Event‑driven architecture
• Data pipelines