Product Leader | Enterprise AI, Data & Cloud Platforms

Established AEM launch-readiness controls across nine operational domains, including a cross-functional readiness checklist and ownership model for go-live decisions. Built shared measurement approaches using Power BI and Excel for adoption, approved-asset reuse, review time, revisions, and delivery efficiency.

Defined implementation architecture and operating models for Script-to-Screen, including identities, schemas, failure handling, storage, review routing, and support ownership. Partnered with Procurement, Legal, Security, Engineering, Operations, and vendors to enable governed enterprise AI solutions, establish Firefly controls, and improve Frame.io adoption and user confidence.

Deliver AI automation, systems integration, workflow modernization, strategy, and process-improvement services. Develop proposals, solution scopes, pricing, implementation roadmaps, and operating models for cloud contact centers, CRM integrations, business-process automation, and managed technology services.

Built sales and marketing operating processes covering target customer profiles, sales-agent onboarding, scripts, lead generation, service positioning, and automated LinkedIn content workflows. Coordinate contractors, sales agents, vendors, and client stakeholders from discovery through delivery planning and operational handoff.

Led concurrent AWS, DevOps, data, analytics, infrastructure, security, and ServiceOps programs across four organizations. Managed scope, schedules, risks, vendors, executive reporting, and modernization initiatives across cloud and data technologies.

Consolidated Slab and Pivotal Tracker into Jira and Confluence, automating time, cost, KPI, prioritization, and PERT workflows to improve efficiency and forecasting accuracy. Led Lean redesign, HITRUST remediation, vendor security reviews, incident-response planning, and resilience tabletop exercises.

Transitioned the organization to Agile delivery and led Scrum, backlog refinement, stakeholder planning, roadmaps, requirements, architecture direction, and delivery for AI advisory and MVP initiatives. Improved project timelines across image-recognition, recommendation, and automation products.

Directed IBM Cloud inference and ingestion architecture and developed training on cloud infrastructure, machine-learning concepts, model lifecycle, and deployment. Launched the HairNetAI computer-vision MVP from scope through pilot while coordinating design, engineering, validation, and stakeholder decisions.

Delivered an industrial edge-to-cloud module pilot and secured required certifications by coordinating embedded hardware, firmware, telemetry, manufacturing, validation, and regulatory testing. Managed prototype builds, suppliers, EMS partners, contract manufacturers, and production-readiness activities.

Engineered Helium-connected sensor networks and ARM Cortex-M/RTOS devices for real-time analytics, monitoring, and secure edge-to-cloud data exchange. Directed AWS ECS and star-schema supply-chain automation MVPs that reduced operating costs and developed blockchain validation prototypes for device telemetry verification.