
201 - 500 employees
Founded 2020
☁️ SaaS
🤝 B2B
🏢 Enterprise
💰 $15M Series A - OpenLoop Health on 2023-03
SaaS • B2B • Enterprise
OpenLoop is a white-label telehealth platform and managed services provider that helps organizations launch and scale virtual care programs. It combines SaaS-based, brandable technology (scheduling, booking, payments, EHR/API integrations) with clinical staffing, credentialing, payer coverage and RCM, regulatory/legal support, and 24/7 patient support. OpenLoop serves health plans, hospitals and health systems, retailers, employers and digital health companies with AI-powered operations, a nationwide clinician network and broad insurance coverage including Medicare and Medicaid.
🔥 12 hours ago
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201 - 500 employees
Founded 2020
☁️ SaaS
🤝 B2B
🏢 Enterprise
💰 $15M Series A - OpenLoop Health on 2023-03
SaaS • B2B • Enterprise
OpenLoop is a white-label telehealth platform and managed services provider that helps organizations launch and scale virtual care programs. It combines SaaS-based, brandable technology (scheduling, booking, payments, EHR/API integrations) with clinical staffing, credentialing, payer coverage and RCM, regulatory/legal support, and 24/7 patient support. OpenLoop serves health plans, hospitals and health systems, retailers, employers and digital health companies with AI-powered operations, a nationwide clinician network and broad insurance coverage including Medicare and Medicaid.
• Own and operate OpenLoop's AI governance program end-to-end — use-case intake, risk triage and scoring, the AI Use Case Register, issue tracking, and the AI Governance Council review cadence. • Author and evolve OpenLoop's AI governance standard — the scoring rubric, risk taxonomy, and review framework — keeping it current with evolving AI risk frameworks and the U.S. regulatory landscape, including new federal executive orders and emerging state AI laws. • Run intake and review to SLA: assess new AI use cases, document risk and regulatory exposure, set conditions of approval, and drive findings to closure. • Prepare and lead AI Governance Council sessions — agenda, materials, and recommendations — so decisions get made, recorded, and acted on without escalation. • Help stand up and then run OpenLoop's data governance program on the same model — the Data Governance Council, the data governance standard, the enterprise data classification scheme, and the data ownership and stewardship model. • Measure adherence to the data governance standard across the operating teams, and report clearly where the organization is and is not meeting it. • Partner with the teams that operate data day to day — Privacy, Data Security, Data Protection (DLP), Data Platform, and Data Engineering & Analytics — setting the standards they run against and measuring whether they're met. • Govern the data that feeds AI systems as a priority slice of both programs — provenance, lineage, classification, and quality of training and inference data — so models are built on trustworthy, appropriately handled data. • Assess AI vendor and model risk in partnership with Third-Party Risk, Security, and Legal — including standalone AI tools and AI features embedded in existing vendors. • Maintain AI and data governance metrics, dashboards, and reporting. Translate AI and data risk posture into language the leadership team and board can act on. • Support SOC 2, HITRUST, and HIPAA assurance activities related to AI and data governance controls. • Use AI to run the program — automate your own governance workflows for intake, scoring, evidence gathering, and reporting, and keep improving them. • Other duties as assigned.
• 5-7 years experience in GRC (governance, risk and compliance), with at least 2 years hands-on in AI/ML governance or AI risk management. • Experience with AI and data governance, including oversight of data flows, and third-party risks. • Experience with workflow automation, bringing specific hands-on experience with agentic tools like Claude Code. • Experience with AI governance frameworks such as the NIST AI RMF, and the U.S. AI regulatory landscape, including new federal executive orders and emerging state AI laws. • Experience building or operating an AI use-case intake, risk-scoring, and review process — registers, review boards, or AI governance councils. • Working knowledge of a data governance operating model — classification, ownership and stewardship, lineage, and quality — ideally aligned to CDMC or DAMA-DMBOK. • Proven experience standing up and running a data governance program • Ability to author governance standards and risk taxonomies, and measuring adherence. • Experience with healthcare data, HIPAA, and PHI handling. • Strong analytical and writing skills — you can build a rubric, score a use case, and produce executive-ready reporting. • Experienced with being an autonomous team player, in a lean, fast-moving environment.
• Health insurance • 401(k) matching • Flexible work arrangements • Professional development opportunities
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