Software Engineer II

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.

For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.

Job Overview

The Software Engineer is responsible for coding, testing and implementing products for our HRS Platform Team, which is increasingly focused on agentic and AI-driven engineering. This role is for engineers who have meaningfully adapted their day-to-day workflow (design, coding, testing and debugging) around AI-assisted and agentic development tools and who can bring that fluency to raise the bar for the broader team. Responsibilities include reviewing functional and technical requirements, performing research, designing solutions and developing code in a variety of programming languages for a Web + AI -based enterprise application.

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.