.Net AI Architect | Onsite

Posted 9 Hours Ago
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2 Locations
In-Office or Remote
64K-224K Annually
Senior level
Agency • Information Technology
The Role
Design and own an agentic AI content-generation platform on Azure using .NET and Azure OpenAI. Architect event-driven, multitenant agent systems, implement RAG pipelines, integrate data sources and WordPress headless publishing, ensure security/compliance, and collaborate on CI/CD and IaC for scalable, observable deployments.
Summary Generated by Built In

Key Responsibilities 

Solution Architecture: Define and own the end-to-end architecture for an agentic AI content generation platform, leveraging Azure services, .NET, and OpenAI. 

Agent-Oriented Design: Architect modular, event-driven agents for content generation  

Data Integration: Build connectors to third-party APIs  and harmonize structured/unstructured data for LLM prompts. 

AI Orchestration: Design pipelines using Retrieval-Augmented Generation (RAG) patterns with Azure Cognitive Search and Azure OpenAI. 

Headless Publishing: Integrate with WordPress via REST/GraphQL APIs for seamless page creation, preview, and publishing. 

Scalability & Performance: Design for multitenancy, high-availability, and elastic scale using Azure Functions, Service Bus, and Durable Functions. 

Security & Governance: Implement secure API authentication, rate-limiting, observability, and prompt logging for compliance and auditability. 

DevOps & Delivery: Collaborate with the DevOps team to implement CI/CD pipelines, IaC (Bicep/ARM/Terraform), and automated testing. 


Required Skills 

 

Area 

Skills 

.NET Core 

7.0+, ASP.NET Core APIs, Dependency Injection 

Cloud 

Azure Functions, Event Grid, Service Bus, Blob Storage, Cognitive Search 

AI/LLM 

Azure OpenAI, RAG pattern, prompt engineering 

Data 

REST APIs, SQL Server, Cosmos DB, external API consumption 

DevOps 

Azure DevOps, GitHub Actions, Bicep/ARM 

Architecture 

Event-driven, agent-based systems, microservices, API-first design 

Security 

OAuth2, managed identity, secure API access 

Integration 

WordPress REST/GraphQL APIs, CRM data, analytics ingestion 

Documentation 

Mermaid diagrams, architectural decision records (ADR), Swagger/OpenAPI specs 


Preferred Experience 

Experience building content automation or AI-based CMS tools 

Familiarity with SEO strategy, schema.org, and headless CMS patterns 

Experience with multi-brand/multi-site architecture 

Understanding of semantic search, vector DBs, and embeddings 


Compensation, Benefits and Duration

Minimum Compensation: USD 64,000
Maximum Compensation: USD 224,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post

Skills Required

  • .NET Core 7.0+ and ASP.NET Core APIs (Dependency Injection)
  • Azure Functions and Durable Functions
  • Event Grid and Azure Service Bus
  • Azure Blob Storage
  • Azure Cognitive Search
  • Azure OpenAI / OpenAI and RAG pattern implementation
  • Prompt engineering for LLMs
  • REST API integration and external API consumption
  • WordPress REST/GraphQL API integration (headless publishing)
  • SQL Server
  • Cosmos DB
  • Azure DevOps or GitHub Actions CI/CD
  • IaC: Bicep / ARM (Terraform mentioned in responsibilities)
  • Event-driven, agent-based, microservices and API-first architecture experience
  • OAuth2 and managed identity for secure API access
  • Observability, rate-limiting, prompt logging and security governance
  • Architectural documentation: Mermaid diagrams, ADRs, Swagger/OpenAPI specs
  • Experience building content automation or AI-based CMS tools
  • Familiarity with SEO strategy, schema.org, and headless CMS patterns
  • Experience with multi-brand/multi-site architecture
  • Understanding of semantic search, vector DBs, and embeddings
  • Experience with Terraform (infrastructure as code)
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