Lead AI Engineer

Job Title: Lead AI Engineer

Reports To: Director, Digital Transformation

Department/Group: Digital Transformation

Position Type: Full Time

Location: Pogue Construction Company McKinney, TX

Salary Range: $ Based on Experience

Applications Accepted By: Until position is filled

Pogue Construction Company, 1512 Bray Central, McKinney, TX 75069

Email: [email protected]

Experience

5+ years' professional software development experience, including full-stack web application development & 2+ years building & supporting AI or LLM-integrated applications in production. Demonstrated experience taking applications from prototype through production & ongoing support.

Education

Bachelor's degree in computer science, software engineering, information systems or a related field, or commensurate experience

Summary

The Lead AI Engineer delivers & operationalizes Pogue's enterprise AI capabilities, taking approved backlog items & validated prototypes through production as secure, reliable, well-documented solutions. Working as part of Pogue's AI production team, this individual leads secure retrieval, application integrations, reusable AI services & the engineering needed to deploy & support them. Full-stack development is a core skill of the role, used to carry applications from prototype through production.

This is a hands-on technical leadership role. This individual partners closely with Pogue's Enterprise Data Architect, who leads the enterprise data architecture, governed data products, data pipelines & shared semantic models, and builds on that foundation in Microsoft Fabric & the enterprise knowledge foundation. This individual leads solution design through review with Pogue's Principal Solutions Architect, provides technical guidance to the AI production team, and partners directly with business owners so that what gets built is actually used.

Primary Responsibilities

Required Skills/Expectations

Enterprise AI Delivery & Reusable Services:

• Deliver & operationalize Pogue's enterprise AI capabilities, such as enterprise search, internal assistants, agents & workflow automation
• Build & maintain reusable AI services (model access, retrieval, evaluation, logging & guardrails) that Pogue applications share
• Integrate approved models through APIs, structured outputs & tool calling using Azure OpenAI or Azure AI Foundry
• Break approved backlog items into requirements, designs, acceptance criteria & small, measurable releases
• Lead design review with the Principal Solutions Architect before development & carry approved designs through release & support

Secure Retrieval & Application Integration:

• Lead secure retrieval across structured data & approved documents, including permission-aware access, citations, versions, effective dates & retrieval quality
• Lead application integrations that connect Pogue applications to enterprise systems, Fabric data & AI services through secure APIs
• Partner with the Enterprise Data Architect, building on governed data products & shared semantic models in Microsoft Fabric
• Partner with the Enterprise Data Architect on Pogue's knowledge foundation, bringing application needs into objects, relationships & definitions
• Build only on validated Gold-layer data; raise data gaps to the data team rather than working around them

Full-Stack Development & Production Readiness:

• Take validated prototypes, including SME-built prototypes, from prototype through production as maintainable applications & reusable components
• Build responsive, accessible front ends in Blazor & C#, using TypeScript or JavaScript where needed
• Build back-end services & REST APIs in C# & .NET
• Deploy, monitor & support solutions on Azure, including Azure Static Web Apps, with CI/CD & Microsoft Entra ID authentication

Quality, Security & Trust:

• Set the team's standards for documentation, testing, code review, deployment, monitoring & operating runbooks
• Design evaluations for accuracy, failure modes, access behavior, latency, cost & usefulness; own release recommendations
• Enforce Pogue's identity, role-based access, data-classification, approved-model, logging & human-approval requirements
• Apply secure development practices across front end, back end & AI, including prompt-injection, data-leakage & agent-permission risks

Business Partnership & Adoption:

• Work directly with business owners & subject-matter experts to understand the decision or workflow before selecting a technical approach
• Explain tradeoffs & feasibility in plain language to technical & nontechnical stakeholders
• Support adoption with concise guides, training materials & responsive follow-through after launc
• Support the AI Champions Network as solutions roll out to project teams

Technical Leadership:

• Provide technical guidance to the AI production team, including Associate AI Engineers & interns, through pairing, code review & design feedback
• Establish reusable engineering patterns & recommend improvements to team tooling & standards

Required Skills/Expectations

• Hands-on experience building & operating LLM applications in production, including RAG, embeddings, tool calling & evaluation
• Experience designing reusable services or shared platform components
• Able to explain a technical design, the decisions personally made, the tradeoffs & how the result was validated
• Strong command of REST API design & enterprise integration
• Advanced SQL & relational data modeling
• Working knowledge of Microsoft Fabric, semantic models & governed data products
• Highly analytical thinker
• Advanced C# & .NET, including ASP.NET Core web APIs
• Production front-end experience in Blazor or a comparable component framework
• TypeScript or JavaScript, HTML & CSS, responsive & accessible design
• Advanced proficiency writing, reviewing & troubleshooting code in VS Code
• Git-based collaboration, automated testing & CI/CD
• Experience deploying & supporting applications in Azure or a comparable cloud
• Secure handling of credentials & data, including identity & role-based access
• Highly organized & detail oriented
• Clear written communication
• Able to relate to & communicate with a diverse group of professionals
• Internal & external customer service
• Ability to work individually & as part of a team
• Self-motivated & driven
• Positive Attitude
• Team Player
• Learn & Grow
• Mentor & Teacher
• Curious & self-directed
• Minimum 20 hrs of Continued Education (yearly)

Helpful, Not Required

• Azure AI Search, Azure API Management, OneLake or Power BI
• React or another JavaScript front-end framework
• Agents, MCP integrations, workflow automation, prompt or model lifecycle management
• Knowledge representation, semantic modeling, enterprise ontologies or knowledge graphs — including Protégé, OWL, RDF or SPARQL
• Containerized services, infrastructure as code or cost management
• Experience with construction & project-control systems, or in another operationally complex industry

Oversight (individuals)

• None — individual contributor; provides technical guidance to the AI production team