AI Automation Engineer

Matrix Medical Management•Bellaire, TX

6h•Onsite

About The Position

Matrix Medical Management is looking for a full-time AI Automation Engineer to join our team in our Bellaire office! The AI and Automation Engineer is responsible for designing, developing, testing, deploying, and maintaining AI and automation solutions across the enterprise. This is a hands-on individual contributor engineering role, with primary responsibility for delivering production-grade solutions. The role builds Microsoft Power Platform solutions (Power Apps, Power Automate, Power BI), configures Microsoft Dynamics 365, enables Microsoft 365 Copilot capabilities, and develops AI-powered workflows in close partnership with Operations. The AI and Automation Engineer is also responsible for supporting alignment of AI initiatives with organizational priorities, governance requirements, and operational readiness within a healthcare environment.

Requirements

Knowledge of healthcare operations, including clinical and administrative workflows, and how AI and digital tools can be applied to improve them
Understanding of AI applications in business environments, including use cases, limitations, risks (e.g., bias, hallucination), and responsible AI principles
Knowledge of digital transformation, process improvement methodologies, and technology adoption lifecycle
Knowledge of data privacy, security, HIPAA requirements, and AI governance, risk, and compliance frameworks
Strong program and project management skills, including managing multiple concurrent initiatives and driving execution from pilot through enterprise scale
Process improvement and workflow optimization skills, with a focus on operational efficiency and user experience
Ability to evaluate and prioritize opportunities using business case development, ROI analysis, risk assessment, and KPI-driven performance tracking
Vendor evaluation and management skills, including assessment of third-party AI solutions
Strong communication skills, including the ability to translate complex technical concepts into clear business language
Strong stakeholder engagement skills, with the ability to navigate complex organizational structures and drive cross functional alignment
Ability to translate business needs into scalable, practical AI-enabled solutions
Ability to operate effectively in ambiguity and a rapidly evolving technology landscape while balancing innovation, risk, compliance, and operational constraints
Ability to work across business, technical, and governance stakeholders to ensure alignment and accountability from pilot through full-scale implementation
Demonstrated hands-on experience building in the Microsoft Power Platform: Power Apps (canvas and model driven), Power Automate, and Power BI (data modeling, DAX, row-level security, publishing)
Working proficiency in Microsoft Dynamics 365 configuration and customization — entities, business process flows, security roles, and integrations
Working proficiency with Microsoft 365 Copilot, including rollout, governance, and user enablement
Hands-on experience designing Claude-based (or comparable LLM) workflows — prompt engineering, prompt libraries, API usage, and connector or orchestration patterns
Light-to-moderate scripting ability (Python and/or JavaScript) for integrations, data transformation, and automation glue
Familiarity with Microsoft identity, access, and audit tooling (Entra ID / Active Directory, Purview, M365 audit logs); working knowledge of healthcare operations, credentialing, and revenue cycle basics
Bachelor’s degree in Information Systems, Computer Science, or Health Informatics also qualify; equivalent demonstrated hands-on experience may substitute for a degree
Five (5) years of experience in business process improvement, digital transformation, product/program management, or related roles
At least two (2) of the five (5) years of experience should include shipping production solutions on the Microsoft Power Platform and/or with LLMs (Claude or comparable); a portfolio or work samples are strongly preferred at interview

Nice To Haves

A portfolio or work samples are strongly preferred at interview

Responsibilities

Build, manage, and continuously refine a pipeline of AI use cases aligned to business priorities.
Partner with stakeholders to identify high-impact opportunities for AI-driven efficiency, quality, and growth.
Evaluate opportunities based on feasibility, risk, and return on investment.
Coordinate cross-functional review of AI initiatives with legal, compliance, IT, security, and data teams.
Ensure adherence to organizational policies, regulatory requirements, and ethical AI standards.
Support the development and enforcement of AI governance frameworks.
Assess and recommend third-party AI solutions in partnership with procurement and IT.
Monitor vendor performance and alignment with business needs.
Lead workflow-focused implementation of AI solutions in partnership with business and technical teams.
Design, build, and maintain Microsoft Power Apps and Power Automate flows that streamline operational workflows, including credentialing, intake, referral management, internal requests, and cross-team handoffs.
Develop Power BI dashboards for executive, operations, finance, and clinical leadership, with appropriate row-level security and governed data sources.
Configure and extend Microsoft Dynamics 365 for internal business use cases, including referral tracking, case management, and patient-relationship workflows.
Lead Microsoft 365 Copilot rollout, enablement, and measurement — train teams, build internal playbooks, and track utilization and time-saved metrics.
Design and maintain AI-based workflows for HR, Finance, Legal, and executive teams, supporting use cases such as policy drafting, contract review, and document analysis.
Build lightweight integrations (Python, JavaScript, or low-code) between AI tools and internal systems, with appropriate safeguards for PHI, least-privilege access, audit logging, and applicable vendor agreements.
Drive change management and user adoption efforts to ensure successful deployment.
Develop best practices and playbooks for scaling AI solutions across teams.
Track outcomes, performance metrics, and business impact of AI implementations.
Monitor post-go-live performance and identify opportunities for optimization.
Report on AI program effectiveness to leadership.
Perform other related tasks as needed.