Overview

When it comes to IT solution providers, there are a lot of choices. But when it comes to providers with innovative and differentiating end-to-end service offerings, there’s only one: Zones – First Choice for IT.TM

Responsibilities

• Company Overview
• When it comes to IT solution providers, there are a lot of choices. But when it comes to providers with innovative and differentiating end-to-end service offerings, there’s only one: Zones – First Choice for IT.TM
• Zones, LLC on Twitter (Zones), LinkedIn, and Facebook.
• This is deliberately not a traditional full-stack developer role. Most employees bringing us problems are not trying to become developers; they have valuable process knowledge and need someone who can build on their behalf, quickly and safely. The role therefore combines product discovery, AI engineering, quality ownership, deployment and continuous improvement in one person, so that accountability is not fragmented across a chain of handoffs.
• Architecture, Security, Data and Quality Engineering specialists still participate, sized to the risk of the product being built.
• Full-stack engineering experience across interfaces, services and databases, with products you personally took into production.
• Applied AI engineering, including retrieval-augmented generation and agentic workflows, and fluency with AI-assisted development tooling and coding assistants.
• API and systems integration experience in an enterprise environment, including work against existing line-of-business systems.
• Stakeholder translation: the ability to sit with a business owner, frame the problem, and convert an ambiguous request into requirements, a bounded scope and a success measure.
• Engineer-level quality ownership: test scenario design, data and edge-case validation, load testing, UAT coordination and defect resolution.
• Deployment and operations: controlled CI/CD pipelines, source-control discipline, monitoring, runbooks and post-launch support.
• Comfort working inside governance rather than around it: identity and access, data protection, dependency review and human oversight sized to the risk of the product.
• Strong .NET engineering: C# and ASP.NET Core for services and web APIs, with attention to performance, security, dependency management and testability.
• Contemporary front-end development with React and TypeScript: component design, state management, form and validation patterns, and responsive, accessible interfaces.
• Database engineering: relational data modeling in SQL Server, stored procedures, query and index tuning, schema migrations, and disciplined handling of production and test data.
• Cloud and DevOps fundamentals on Azure: app services and containers, secret and key management, environment configuration, and build and release pipelines in Azure DevOps or GitHub.
• Automated testing across the stack: unit and integration tests for .NET services, component and end-to-end tests for the front end, and test data management.

Qualifications

• Microsoft ecosystem depth: .Net, Azure. D365 experience is a plus.
• Experience with Azure Foundry, GitHub Copilot, Copilot Studio, Power Automate, Power Apps and agent platforms, and the judgement to know when a low-code path is the right answer.
• A record of building reusable platform components rather than disconnected applications: identity, role-based access, audit logging, notifications, approvals, file storage, API patterns, observability and cost telemetry.
• Exposure to finance operations tooling, partner and employee portals, or workflow modernization is a plus.
• Experience evaluating models, coding tools and open-source components under security and maintainability review.
• Integration experience with Dynamics 365 Finance and Operations, ecommerce platforms or comparable line-of-business systems.
• Working knowledge of Entity Framework Core, REST and messaging patterns, background jobs and caching for internal applications at modest scale.
• Exposure to Python alongside the .NET stack for AI and data work: embeddings, vector stores and evaluation of model output.