Technical Program Manager

WM•Houston, TX

About The Position

The Technical Program Manager plays a crucial role at the intersection of business strategy, technology, and product innovation within the organization. This individual will take ownership of two mission-critical platforms: an AI-driven vendor risk solution and an AI-driven integrated contract lifecycle management (CLM) tool. The ideal candidate is passionate about artificial intelligence and its transformative potential for governance, risk, and compliance (GRC) as well as contract operations. They should bring a blend of technical acumen, product sensibility, business understanding, and stakeholder management skills.

Requirements

Bachelor’s Degree (accredited) in Computer Science, Information Systems, Engineering, Business Administration, or related field.
7 years of experience as a Product Owner, Product Manager, or similar role with direct accountability for technical product delivery.
Hands-on experience with AI or machine learning projects, ideally in risk management or contract management domains.
Strong technical acumen including understanding of APIs, data modeling, cloud platforms, and AI/ML frameworks.
Proven track record managing products in an Agile/Scrum environment.
Excellent communication, negotiation, and stakeholder management skills.
Familiarity with regulatory requirements affecting data security and privacy.
Ability to balance strategic thinking with tactical execution.
Expert communication skills throughout an organization

Nice To Haves

Master’s Degree preferred.
Experience with vendor risk management and/or contract lifecycle management solutions.
Practical exposure to SaaS product development and cloud-based deployments.
Knowledge of the ethical considerations and limitations of AI in enterprise environments.
Ability to translate complex technical concepts into clear business requirements.
Innovative mindset with keen curiosity for industry trends and emerging technologies.
Adaptability to thrive in a fast-paced, cross-disciplinary environment.

Responsibilities

Product Vision & Strategy: Define and articulate the vision for both the AI-driven vendor risk solution and the AI-driven CLM tool in alignment with organizational goals and industry best practices. Develop and maintain product roadmaps that prioritize features, enhancements, and technical debt reduction. Champion AI capabilities that drive automation, predictive risk analysis, smart contract authoring, and analytics.
Stakeholder Engagement: Collaborate with cross-functional teams including engineering, data science, legal, compliance, procurement, and vendor management. Gather and analyze feedback from internal stakeholders, external clients, and market research to inform product direction. Communicate product vision, strategy, and release timelines effectively across all levels of the organization.
Backlog Management: Own and prioritize product backlogs for both platforms, ensuring that user stories and technical requirements are clearly documented, actionable, and aligned with business goals. Work closely with Agile teams to refine backlogs, define acceptance criteria, and balance the need for speed with quality and regulatory compliance. Facilitate sprint planning, stand-ups, reviews, and retrospectives as needed.
AI Integration & Enablement: Drive the integration and optimization of AI capabilities within both the vendor risk and CLM solutions, ensuring scalability, security, and ethical use of AI. Evaluate and select appropriate AI models and frameworks in partnership with data scientists and engineers. Monitor AI performance and recommend improvements to continuously elevate solution value.
Vendor Risk Solution Management: Oversee the end-to-end lifecycle of the AI-driven vendor risk platform—from requirements gathering, design, and development to deployment and ongoing improvement. Ensure the solution proactively identifies, assesses, and mitigates third-party risks leveraging AI-powered automation and analytics. Establish metrics and KPIs for risk detection accuracy, response time, and regulatory compliance. Stay abreast of evolving vendor risk management industry trends and regulations.
Contract Lifecycle Management Tool Oversight: Actively manage the AI-driven CLM tool, ensuring seamless integration with other enterprise systems (ERP, CRM, legal databases, etc.). Drive development of features such as automated contract drafting, clause recognition, smart approvals, and AI-based risk scoring. Continuously improves user experience for legal, procurement, and business teams. Track metrics for contract cycle time, compliance rates, and user adoption.
Compliance, Security & Data Privacy: Ensure both solutions meet relevant regulatory requirements (GDPR, CCPA, HIPAA, PCI DSS, etc.) and internal governance standards. Work with Information Security teams to embed robust security controls in product design, especially for sensitive contract and vendor data. Proactively address ethical AI considerations and data privacy concerns in all product decisions.
Continuous Improvement & Innovation: Champion a culture of experimentation, feedback, and rapid iteration for both platforms. Monitor product analytics to identify areas for enhancement or innovation. Explore emerging technologies (such as Generative AI, Natural Language Processing, Blockchain) that can augment solution capabilities.
Reporting & Controls Responsibilities: Establish and own clear reporting frameworks to monitor key performance indicators, compliance objectives, and operational metrics across both legal and procurement platforms. Collaborate with Business Intelligence Team to develop dashboards and executive reports that provide actionable insights into system usage, contract lifecycle management, and risk exposure. Establish regular reporting cadence to inform supply chain, risk management, and shared services leadership on program progress, compliance, and efficiency. Collaborate with cross-functional teams to implement effective internal controls that safeguard sensitive data, ensure process integrity, and support audit readiness. Continuously review and enhance control mechanisms to respond to evolving regulatory environments and technology standards. Facilitate transparent communication regarding control performance and incident management, driving accountability and rapid resolution of any identified gaps or breaches.