Key responsibilities
Engineering
Design, build, test and ship full-stack features in C#/.NET, ASP.NET Core Web APIs, SQL and a modern web front end.
Write code that meets design specifications, follows team standards, and is easy to maintain.
Review functional and technical requirements, research options, and propose designs. Write or contribute to design documents.
Join design sessions and code reviews.
AI-assisted engineering
Use AI-assisted and agentic development tools in daily work, including code generation, coding agents, AI code review and test generation, to improve both speed and quality.
Get reliable, production-quality output from agentic tools through good context engineering: agent instructions, skills, repo conventions and guardrails.
Coach teammates on effective and responsible AI tool use, including review discipline, security and data-handling rules.
AI in the product
Build and integrate LLM features into Tracker I-9, such as document extraction, RAG, agents and tool use, using Azure OpenAI and related Azure AI services.
Add observability, evaluation and cost and latency monitoring to AI features. Make sure they meet compliance, privacy and security requirements for employee PII.
Quality and delivery
Do unit, automation and peer testing so features ship fully tested.
Ship through CI/CD on Azure DevOps, and help improve pipelines and engineering processes.
Document your work. Give demos, training sessions and presentations when needed.
Work with product, QA, hosting, infrastructure and DBA teams so project requirements are met.
Recommend refactoring, process improvements, tools and new AI-driven development practices.
Required skills and experience
3+ years of professional software development, mostly in C# and .NET (.NET Core).
Strong object-oriented design, design patterns and SOLID principles.
ASP.NET Core and MVC, building RESTful Web APIs, and validation libraries such as FluentValidation.
3+ years of SQL and relational databases (Azure SQL / SQL Server), including query tuning, plus an ORM such as Entity Framework Core or Dapper.
Front-end development with HTML, CSS, JavaScript/TypeScript and a modern framework (Angular preferred). Experience with Bootstrap and jQuery is useful for legacy modules.
Cloud development on Microsoft Azure: App Service, Functions, Storage, Key Vault and Managed Identity.
CI/CD and Git on Azure DevOps (Repos, Pipelines, Boards).
Unit testing and mocking with NUnit or xUnit and Moq or NSubstitute. Familiarity with test automation.
Authentication and security protocols, including OAuth 2.0 and OpenID Connect, and secure coding practices (OWASP).
Hands-on use of AI-assisted engineering tools such as Claude Code, GitHub Copilot or similar in your normal workflow. You should be able to explain specifically how they changed the way you design, code, test and debug.
Understanding of how to manage agent instructions, skills, context and guardrails to get consistent, production-quality results from agentic tools.
At least one shipped project where AI-assisted development clearly sped up delivery or improved quality.
Strong logical reasoning, predictable delivery, and clear written and spoken communication.
We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.
