AI Software Architect

Responsibilities

• Collaborate with BAs and end users to interpret requirements into a technical design through onsite requirements gathering sessions, workshops, and solution design reviews.
• Develop software according to end user requirements and quality standards.
• Identify, document and implement programming patterns and set standards.
• Perform code reviews to enforce patterns and standards in our code base while facilitating in-person knowledge sharing and architectural consistency across teams.
• Lead POCs, design sessions, and pair programming efforts.
• Mentor junior team members.
• Participate in project planning and/or provide accurate estimates on projects/tasks through cross-functional planning meetings and stakeholder alignment discussions.
• Participate in Story Card Grooming and Sprint Planning as requested.
• Be available as needed to support production deployments.
• Possess strong organizational and process analysis skills.
• Effectively communicate both orally and in writing and manage multiple assignments and priorities.
• Actively teach best practices and new technologies.
• Hold teaching sessions at least once a year.
• Facilitate daily standups and lead sprint demos as needed.
• Assist managing the Azure DevOps task board as needed.
• Assist with onboarding and training new resources.
• Support, troubleshoot and resolve production issues, including facilitating in-person incident response discussions and cross-functional problem resolution when required.
• Demonstrate willingness to work on your craft and take initiative in learning new skills.
• Other duties as assigned.

Qualifications

• Subject Matter Expert with Visual Studio, GIT and Azure DevOps
• 10+ years of application development experience across the following technologies:
• .Net Framework/Core
• Angular
• C#
• JSON
• SCSS/SASS
• SQL
• Test Driven Development/Unit Testing
• Typescript, ES6
• Web API/Rest
• Agile Methodology
• Asynchronous Programming
• Azure Data Bricks
• Azure Data Factory
• Azure Functions
• Azure Logic Apps
• Azure PAAS
• Browser Compatibility Testing
• CQRS Pattern
• Dependency Injection
• Entity Framework & LINQ
• MicroServices
• OData
• Python
• In addition to core software architecture duties, this position will lead the design, integration, and governance of AI/ML-driven solutions across the application portfolio, ensuring responsible and scalable adoption of AI capabilities.
• Additional Responsibilities:
• Architect and design solutions incorporating AI/ML components, including LLM-based features, intelligent automation, and predictive models.
• Evaluate and select appropriate AI frameworks, models, and platforms (e.g., Azure AI/OpenAI services, LangChain, vector databases) based on business requirements and technical constraints.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines, prompt engineering strategies, and model orchestration patterns.
• Establish patterns and standards for responsible AI use, including data privacy, model governance, bias mitigation, and explainability.
• Collaborate with data engineering and data science teams to integrate AI/ML models into production applications and CI/CD pipelines.
• Design scalable architectures for embedding generation, semantic search, and vector storage/retrieval.
• Evaluate build-vs-buy tradeoffs for AI tooling and vendor platforms.
• Monitor AI solution performance, cost, and accuracy in production, and drive continuous improvement.
• Stay current on emerging AI/ML technologies, LLM capabilities, and industry best practices, and evangelize relevant advances to engineering teams.
• Mentor developers on AI-assisted development tools and practices (e.g., AI coding assistants, automated testing/generation tools).
• Partner with security and compliance teams to ensure AI solutions meet regulatory and data governance requirements.
• Additional Basic Qualifications:
• Demonstrated experience architecting or building solutions using Large Language Models (LLMs) and generative AI.
• Experience with prompt engineering, RAG architectures, and vector databases (e.g., Cosmos DB vector search, Pinecone, Azure AI Search).
• Familiarity with AI/ML orchestration frameworks (e.g., LangChain, Semantic Kernel) and MLOps practices.
• Working knowledge of Python-based AI/ML libraries and APIs (e.g., OpenAI SDK, Azure OpenAI, Hugging Face).
• Understanding of responsible AI principles: data privacy, model bias, explainability, and governance.
• Experience integrating AI capabilities into cloud-native (Azure) application architectures.
• Education:
• Bachelor’s degree or higher in Computer Science or related degree is preferred.

Benefits

• Not specified