Technical Solutions Architect - Azure, .NET & Generative AI

Technical Solutions Architect - Contract
Location: New York, New York, NY (Hybrid: 3 Days Onsite / 2 Days Remote)

Technical Solutions Architect | AI-Enabled Enterprise Architecture, .NET, Angular, Microsoft Azure, Azure OpenAI, and Enterprise Integration

Role Overview
We are seeking a highly motivated Technical Solutions Architect with 12+ years of software development experience, including 5+ years as a Technical Solutions Architect, to lead the architecture, design, and technical governance of an AI-powered enterprise application platform. The role will define the end-to-end architecture, integration strategy, and code quality standards for a solution built on .NET, Angular, Microsoft Azure, Azure OpenAI, and Agentic AI technologies, with integrations to ServiceNow, Azure DevOps, and other enterprise systems.

This is a hands-on architecture leadership role with approximately 30% hands-on responsibility for proofs of concept, reference implementations, architecture validation, and code reviews. The role will define and enforce coding standards, architecture patterns, security controls, scalability principles, AI governance standards, accessibility requirements, and automated quality gates to support secure, resilient, and maintainable enterprise solutions.

Key Responsibilities
Design end-to-end enterprise solutions on Microsoft Azure using .NET services and Angular front ends.
Design and govern the applications AI architecture, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, prompt orchestration, model integration, AI observability, model evaluation, and Human-in-the-Loop controls.
Select appropriate Azure services, including App Service, Functions, AKS, Container Apps, API Management, Service Bus, Event Hubs, Azure SQL, Cosmos DB, Key Vault, and Azure OpenAI.
Design for performance, high availability, disaster recovery, cost optimization, security, scalability, and resilience before development begins.
Define the data architecture, including data models, caching, storage, and integration patterns.
Design integrations with ServiceNow, Azure DevOps, and enterprise systems, including APIs, authentication, data flow, and error handling.
Build proofs of concept and evaluate tools and vendors before finalizing designs.
Create and maintain architecture documents, diagrams, decision records, coding standards, and reference implementations.
Define coding standards for C#, .NET, Angular, TypeScript, JavaScript, Python, SQL, PowerShell, and YAML, including WCAG accessibility and UI performance.
Lead code reviews and enforce pull-request quality gates.
Establish standards and governance for Responsible AI, model lifecycle management, AI security, AI coding assistants, and review of AI-generated code.
Design the Azure DevOps pipeline strategy with static analysis, automated testing, security scans, code coverage, and regression testing.
Identify technical debt, recommend a paydown plan, lead design-related root-cause analysis, mentor developers, and participate in technical interviews.

Required Skills & Experience
12+ years in software development, including 5+ years as a Technical Solutions Architect for multi-system enterprise applications from requirements through production.
Proven experience architecting and delivering AI-enabled enterprise applications, including integration of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents using Azure OpenAI and Azure AI Services.
Production development experience with C#, .NET 8 or later, ASP.NET Core Web API, Entity Framework Core, and SQL Server or Oracle.
Experience building Angular 17 or later and TypeScript front ends, including component design and state management.
Experience designing and operating production workloads on Microsoft Azure, including Docker and Kubernetes (AKS).
Demonstrated application of Microservices Architecture, REST APIs, Event-Driven Architecture, SOLID Principles, and Clean Architecture.
Enterprise integration experience with REST APIs, Webhooks, Messaging Platforms, API Gateways, and Service-to-Service Authentication.
Experience with Azure API Management and Single Sign-On using Microsoft Entra ID or Okta, leveraging SAML, OAuth 2.0, and OpenID Connect.
Experience with Azure DevOps Repos, Boards, Build and Release Pipelines, CI/CD Automation, and Automated Regression Testing, including Infrastructure as Code using Terraform or Bicep.
Strong understanding of Application Security, including OWASP Top 10, Threat Modeling, Secure Coding Practices, and Security-by-Design Principles.
Ability to communicate and present technical architecture decisions, trade-offs, and recommendations to business and technical stakeholders.
Proven experience taking enterprise architectures from requirements through production while maintaining design integrity and code quality.

Preferred Skills & Experience
Experience with AI coding assistants such as GitHub Copilot or Claude Code.
Experience with ServiceNow REST APIs, incidents, change requests, and workflows.
Experience with Application Insights, Azure Monitor, Playwright or Selenium, xUnit, Jasmine, or Jest.
Experience with Python, JavaScript, PowerShell or Bash, and secrets management using HashiCorp Vault or Azure Key Vault.
Utility or energy industry experience, including NERC CIP and SOX compliance.
Experience modernizing legacy .NET Framework applications to the cloud.
Proven experience taking architectures from requirements through production and maintaining design and code quality.

Education and Qualifications
Bachelors Degree or higher in Computer Science, Engineering, Information Systems, or a related field, or equivalent professional experience.
Advanced Azure, cloud, security, or architecture certifications preferred.

What Success Looks Like
Within the first 90 days, coding standards, approved architecture patterns, AI governance standards, and reference architecture are published and adopted.
Static analysis, automated tests, security scans, code coverage, regression quality gates, and AI observability controls are operating in the delivery pipeline.
Designs for ServiceNow and Azure DevOps integrations are reviewed and approved.
Every release proceeds through established quality gates, automated regression runs on every build, and technical debt is actively tracked with an agreed paydown plan.

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