Socure Lead Program Manager drives program management and strategic structure for Socure's enterprise AI initiatives. The role coordinates cross-functional execution and shapes AI enablement and change management.
Responsibilities
Lead program planning and coordination across Internal Transformation, AI-DLC, the Agentic Flywheel and customer-facing AI initiatives. Align stakeholders and track milestones, owners, dependencies and risks, with enablement and change management built into each pillar's plan.
Run portfolio intake and prioritization with executive sponsors and pillar leaders. Bring together business value, team capacity, dependencies and readiness input from the owners; surface tradeoffs and support decisions on sequencing, scope and investment.
Partner with Internal Transformation leaders from workflow discovery and business case through rollout, adoption and benefit realization. Coordinate functional owners and technical teams to redesign work, automate high-value processes and reduce duplicated solutions.
Partner with AI-DLC leaders on project management and enablement, change and adoption plans. Align learning, communications and stakeholder readiness to their roadmap; track commitments and barriers with technical leaders who own implementation.
Partner with Agentic Flywheel leaders on project management, stakeholder alignment and how teams prepare for and adopt new ways of working. Track milestones, dependencies and risks, and shape enablement and change support with Data Science and Engineering leaders.
Run AI governance forums as decision-making and escalation mechanisms. Prepare options and recommendations, secure decisions from accountable owners, track commitments and close blockers across pillars; involve the appropriate technical, risk and investment decision owners.
Report program progress, stakeholder readiness, adoption and business value using measures agreed with pillar leads. Distinguish enablement activity from changes in how people work, and use technical-owner inputs when reporting pillar outcomes.
Shape the enablement and change-management approach across AI pillars. Identify affected audiences, clarify how work will change, and coordinate learning, communications, Champions, manager support and feedback with pillar leads, People/L&D and functional leaders.
Identify shared enablement needs and reusable practices across pillars. Partner with AI Incubation, IT and functional leaders to reduce duplicated efforts, clarify available tools and support, and route access, policy or tooling barriers to the right owners.
Maintain integrated program plans based on pillar leaders' roadmaps, with clear scopes, owners, milestones, resource needs, dependencies and adoption goals. Reconcile timelines and capacity, and escalate risks and decisions before they delay progress.
Qualification
Run the cross-pillar project cadenceA bachelor's degree is requiredAt least 7 years leading complexExperience facilitating governance
Required
Run the cross-pillar project cadence, track commitments and coordinate action on blockers. Maintain clear risks and decisions, and give leadership a concise view of progress, change readiness, adoption, tradeoffs and business value.
Coordinate rollout and operational handoffs with named owners, accessible documentation, knowledge transfer and feedback loops. Ensure teams know what is changing, how to use new capabilities and where to get support after launch.
A bachelor's degree is required. PMP certification or an equivalent program management credential is a plus.
At least 7 years leading complex, cross-functional technology or business transformation programs, independently managing plans, stakeholders and commitments across technical and business workstreams.
Ability to translate strategic priorities into clear program plans, milestones and stakeholder responsibilities, and manage resource needs, dependencies, risks and decisions across concurrent workstreams.
Familiarity with AI and agentic capabilities and how they affect business, software and data-science workflows. Able to ask useful questions, translate technical updates and identify change impacts; engineering or machine-learning specialization is not required.
Evidence of measurable business improvements and sustained adoption. You can agree baselines and success measures with domain owners, distinguish activity from outcomes and use feedback and data to improve program and change plans.
Strong executive communication and technical-to-business translation, including clear decision briefs, stakeholder messages and reporting on progress, dependencies, adoption barriers and business impact.
Experience designing enablement and change approaches for managers, business teams and technical practitioners, connecting learning, communications, support and feedback to day-to-day work.
Experience facilitating governance, resolving ownership conflicts and influencing executive and technical stakeholders without reporting authority, plus a record of coaching colleagues and improving program practices.
