AI Technical Program Manager

RK Industries, LLC•Denver, CO

3d•$170,000 - $185,000•Onsite

About The Position

RK Industries is building an enterprise AI capability on Microsoft technologies to deliver measurable business value. Its governed Modern Data Platform (MDP) integrates ERP and operational data, with plans to mirror it into Microsoft Fabric to support AI and business solutions. The AI Technical Program Manager will build and lead a team of AI engineers and agent developers, own RK’s technical AI roadmap, and remain hands-on in prototyping, solution design, and quality oversight. In partnership with Strategic AI managers, business leaders, the Data team, and external partners, this role identifies opportunities, translates business needs into AI solutions, ensures agents use governed MDP data, and transitions early prototypes into production-ready solutions. The role leads the technical AI team and its operating model, owns technical roadmap and delivery, partners with business stakeholders on workflow discovery and measurable outcomes, and designs and oversees enterprise-grade agents. It also works with the Data team to ground agents in governed MDP and Fabric data, establishes evaluation and Responsible AI practices, and monitors production agents. The position is primarily office-based.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
8+ years of experience in software, data, or AI engineering, including 3+ years building and deploying AI, ML, or LLM-based solutions in an enterprise.
3+ years leading technical teams, including hiring, performance management, and day-to-day delivery.
Track record of owning AI agents or LLM applications end to end, from business problem through production, adoption, and measured value.
Hands-on experience with Microsoft Foundry / Azure AI Foundry and Azure OpenAI, plus Copilot Studio and Microsoft 365 Copilot extensibility.
Deep understanding of enterprise RAG and grounding, including retrieval evaluation, permissions-aware search, and diagnosing wrong or poorly cited answers.
Experience designing agent evaluations, acceptance thresholds, and production monitoring.
Hands-on coding experience in Python and/or C#, plus strong SQL skills.
Disciplined use of AI coding assistants such as GitHub Copilot.
Working knowledge of AI security and governance, including identity, least privilege, prompt injection, auditability, and human-in-the-loop design.
Strong business partnership skills, including process mapping, requirements development, and explaining AI trade-offs to executives and end users.
Regularly stand, sit, walk, talk, hear, and use hands and fingers to operate cameras, computers, and other equipment.
Frequently lift and carry equipment up to 30 pounds.
Occasionally reach, stoop, kneel, climb stairs, or navigate active construction sites.

Nice To Haves

People management experience is strongly preferred.
Microsoft Fabric experience, including OneLake, mirroring, Fabric data agents, semantic models, and row-level security.
Familiarity with dimensional data models (Kimball) and enterprise data warehouses sufficient to work closely with a data architecture team.
Experience with Foundry Agent Service, Model Context Protocol (MCP), multi-agent orchestration, and Foundry Toolkit for VS Code.
Experience with Power Platform, including Power Apps, Power Automate, and Dataverse.
Construction, engineering, or specialty-contracting experience, including document-heavy workflows such as specifications, drawings, submittals, and materials takeoffs.
Experience managing external AI or development partners.
Microsoft certifications such as Azure AI Apps and Agents Developer Associate (AI-103), Azure Solutions Architect Expert (AZ-305), or Fabric Analytics Engineer Associate (DP-600).

Responsibilities

Hire, onboard, develop, and lead a team of AI engineers and agent developers; define roles, write job descriptions, run interviews, set priorities and goals, assign work, conduct code and design reviews, manage performance, and support career development.
Define the team’s operating model for moving work from idea to prototype, production, and support, including handoffs from partners or builders to engineers.
Manage external AI development partners by setting acceptance criteria, reviewing deliverables, and requiring rework or rejecting work that does not meet standards.
Build and maintain RK’s technical AI roadmap, sequencing work by business value, data readiness, and dependencies in partnership with the Director and Strategic AI managers.
Lead technical delivery of AI data chat, from an initial pilot data agent to Teams-based adoption at scale, and support agent-enabled workflows in sandboxes and business solutions.
Select appropriate tools for each use case, including Copilot Studio, Fabric data agents, Microsoft Foundry, Power Platform, or traditional automation; recognize when AI is not appropriate.
Track Microsoft AI and Fabric developments and identify relevant capabilities for RK.
Work with Strategic AI managers and business stakeholders to identify agent opportunities, map processes and workflows, and determine which tasks should be handled by agents versus people.
Translate business needs into requirements, success measures, baselines, and acceptance criteria; commit to outcomes and report progress, risks, and performance honestly.
Design and oversee agents in Microsoft Foundry and Copilot Studio, including tools and functions, enterprise grounding, integrations, and Microsoft 365 or Teams deployment.
Design enterprise RAG solutions for documents such as construction specifications and drawings, including authoritative sources, chunking, metadata, embeddings, hybrid and vector search, permissions, and traceability.
Build prototypes, lightweight coded agents, integrations, and evaluation harnesses using Python, C#, or SQL; use AI coding assistants carefully and validate their output.
Partner with the Data Architect and Data team to ensure agents use governed MDP data mirrored into OneLake, not parallel pipelines from source systems.
Ensure agents use conformed cross-source objects, raise data-model gaps through the MDP intake process, and help define and enforce row-level security and identity pass-through before deployment.
Account for the differences between analytical and operational questions and design solutions around data latency.
Define production-readiness standards, including evaluation datasets, acceptance thresholds, and measures for groundedness, accuracy, task adherence, safety, and user experience.
Design human oversight for agents that act, including appropriate levels of assistance or execution, escalation based on rules or confidence, and feedback loops from human corrections.
Build security and Responsible AI into discovery and delivery, including least-privilege access, prompt-injection defense, safe actions, audit trails, and traceability.
Monitor production agents and respond to performance and risk signals, including rolling back agents or declining use cases when risk outweighs value.
Maintain professionalism, integrity, confidentiality, and discretion; manage assigned projects and deadlines; follow company policies and procedures; support a positive workplace culture; demonstrate organization and attention to detail; and comply with safety requirements while contributing to a safe work environment.