AI Product Engineer (AI-enabled full-stack engineer)

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 is a global Solution Provider of end-to-end IT solutions with an unmatched supply chain. Positioned to be the IT partner you need, Zones, a Minority Business Enterprise (MBE) in business for over 35 years, specializes in Digital Workplace, cloud & Data Center, Networking, Security, and Managed/Professional/Staffing services. Operating in more than 120 countries, leveraging a robust portfolio, and utilizing the highest certification levels from key partners, including Microsoft, Apple, Cisco, Lenovo, Adobe, and more, Zones has mastered the science of building digital infrastructures that change the way business does business ensuring whatever they need, they can Consider IT Done. Follow Zones, LLC on Twitter (Zones), LinkedIn, and Facebook.
Position Overview:
The AI Product Engineer (AI-enabled full-stack engineer) is the Zones Digital is creating an internal AI incubator: a small, accountable team that turns business problems into secure, reusable internal products in days and weeks rather than months. The AI Product Engineer is the person who does that work. You will sit in the central incubator, take prioritized problems from across the enterprise, and carry each one from the first conversation with a business owner through a working prototype, a production decision, and the improvements that follow launch.
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.
What you’ll do as the AI Product Engineer (AI-enabled full-stack engineer):
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.
Modern 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 acros