
51 - 200 employees
🏥 Healthcare
💼 Consulting
📦 Logistics
💰 Pre seed on 2024-01
Healthcare • Consulting • Logistics
Pivotal Health is a healthcare technology company that provides the industry’s only full-service Independent Dispute Resolution (IDR) platform, combining software, data, and white-glove services to help providers secure fair reimbursement from payers. Their scalable, integrated SaaS platform automates IDR workflows, connects with major revenue cycle management systems, and manages eligibility, submissions, and appeals on behalf of provider organizations. Pivotal Health serves hospitals and specialty practices with a results-driven, outcome-aligned business model (paid after client success) and emphasizes transparency, high client retention, and measurable revenue recovery.
🔥 3 minutes ago
🇺🇸 United States – Remote
💵 $210k - $230k / year
⏰ Full Time
🟠 Senior
🔴 Lead
👮♀️ Software Engineering Manager
👻 Ghost score 20%
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51 - 200 employees
🏥 Healthcare
💼 Consulting
📦 Logistics
💰 Pre seed on 2024-01
Healthcare • Consulting • Logistics
Pivotal Health is a healthcare technology company that provides the industry’s only full-service Independent Dispute Resolution (IDR) platform, combining software, data, and white-glove services to help providers secure fair reimbursement from payers. Their scalable, integrated SaaS platform automates IDR workflows, connects with major revenue cycle management systems, and manages eligibility, submissions, and appeals on behalf of provider organizations. Pivotal Health serves hospitals and specialty practices with a results-driven, outcome-aligned business model (paid after client success) and emphasizes transparency, high client retention, and measurable revenue recovery.
• Lead the Case Strategy Engineering team • Own engineering outcomes that improve incremental reimbursement delivered to customers and connect the technical roadmap to customer value and ARR • Own data models, databases, APIs, services, and full-stack workflows applying case strategies throughout the IDR process • Partner with Science and AI Platform teams to move AI and ML capabilities from experimentation into reliable product experiences • Build systems that capture outcomes, surface signals, and feed real-world results into model development and strategy improvement • Set priorities, coach engineers, create accountability, and support rigorous technical debate • Hire engineers and establish organizational roles, ownership boundaries, and operating practices • Turn ambiguous product and technical problems into plans, sequence work, manage dependencies, and ensure consistent delivery • Guide architecture across Python services, GCP infrastructure, data systems, LLM-enabled capabilities, and customer-facing applications • Use AI-enabled development tools to explore ideas, prototype solutions, and contribute directly when useful • Report to the Director of Product Engineering
• 7+ years of experience as an individual contributor building and leading engineering teams in early-stage environments • 2+ years of experience as an engineering manager • Strong individual-contributor foundation and technical depth to guide architecture and evaluate tradeoffs • Experience delivering production AI or ML products, or managing engineering work in partnership with data-science or applied-science teams • Understanding of reliable systems around models, including data pipelines, feedback loops, APIs, monitoring, and product workflows • Ability to lead through ambiguity and imperfect data • Experience managing experienced, opinionated engineering teams • Ability to connect engineering work to business and customer outcomes, including ARR • Ability to communicate technical decisions and create alignment across Engineering, Science, Product, and other partners • Experience in healthcare, provider reimbursement, revenue-cycle management, claims, or Independent Dispute Resolution (extra credit) • Experience with optimization, experimentation, decision systems, strategy models, or feedback-driven ML products (extra credit) • Experience scaling an early engineering team or building production AI systems using Python, GCP, and LLMs (extra credit) • Must be authorized to work in the United States without current or future employer sponsorship
• Equity • Full health, dental, and vision coverage • Retirement savings plan through 401(k) • Flexible time off • Opportunities for company-wide connection and events • Remote and hybrid flexibility varies by role and team
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