Overview
On Site
$DOE
Full Time
Accepts corp to corp applications
Contract - Full Time
Skills
.net
C#
ASP.NET
AZURE
Cloud
Microservices
Architect
Architecture
GenAI
LLM
Agentic AI
Web AP
Enterprise Applications
Job Details
Job Title: .NET Senior Solution Architect (GenAI / Multi-Agent Systems)
Location: Bellevue / Redmond, WA (Onsite USA)
Job Type: Full-Time
Experience Required: 15+ Years
This is a priority role, and we are looking to close the position this week.
Job Description:
We are seeking a highly experienced .NET Senior Solution Architect with strong hands-on expertise in .NET Core, Azure, and GenAI (multi-agent systems).
The ideal candidate will lead architecture, design, and implementation of enterprise-scale, AI-integrated cloud solutions while working closely with cross-functional teams.
Responsibilities:
- Architect and design large-scale applications using .NET Core, C#, ASP.NET, and Azure services.
- Build and integrate GenAI / multi-agent systems into enterprise applications.
- Design and develop microservices-based architectures with a focus on scalability and performance.
- Lead technical discussions, define architectural blueprints, and ensure alignment with business objectives.
- Collaborate with engineering and data science teams to deliver AI-powered solutions.
- Conduct design/code reviews, ensure security and performance standards are met.
- Stay current with the latest trends in AI, LLMs, and agentic AI frameworks.
Required Skills:
- 15+ years of professional experience in .NET architecture and development.
- Expertise in .NET Core, ASP.NET, Web API, C#, and Microservices architecture.
- Proven experience in Azure Cloud Services (App Services, Azure Functions, Logic Apps, Event Hub, etc.).
- Hands-on experience with GenAI technologies and multi-agent system frameworks.
- Strong background in API integration, system design, and performance optimization.
- Excellent problem-solving, communication, and leadership skills.
Nice to Have:
- Experience with AI model orchestration, LLM integration, or Cognitive AI Services.
- Exposure to AI automation frameworks and modern data pipelines.
- Knowledge of Agile methodologies and DevOps practices.
Education:
- Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
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