The Role

Reporting to the CEO, the CTO owns technology strategy and execution across the whole stack: payer connectivity, API infrastructure, normalized data, and intelligence and AI products. This is a hands-on executive role. You'll move between architecture reviews, team leadership, customer conversations, and board discussions, often in the same week.

What You'll Own

• Platform scale. Build for enterprise-level reliability, uptime, throughput, latency, observability, developer experience, and healthy unit economics.
• Data and AI. Turn high-volume transaction data into governed, queryable assets. Chart the path from messy payer inputs to normalized models, customer-facing intelligence, and practical AI.
• Engineering org. Lead as a player-coach. Set decision rights, planning cadence, and delivery practices. Recruit and develop strong engineers, and build a high-trust culture that scales.
• Reliability, quality, and security. Own testing, deployment controls, data validation, incident response, and self-healing systems. Maintain the company's SOC 2 and HIPAA posture as it grows.
• Executive partnership. Work with Product on roadmap, and with Finance, Revenue, Legal, customers, and the board on tradeoffs. Translate technical decisions into business terms.

What You Bring

• 8+ years of technical leadership, including leading engineering at a venture-backed Series A–C company
• Experience as a CTO, VP or Head of Engineering, or senior architect in API-first, data infrastructure, healthtech, or complex automation businesses
• Hands-on depth in mission-critical APIs and production data systems, including pipelines, warehouses or lakehouses, and normalized data models
• Practical experience applying AI, ML, or automation, with good judgment about where it creates lasting value
• Strong command of API design, cloud infrastructure (GCP a plus), CI/CD, observability, data governance, and SOC 2 and HIPAA programs
• A track record of hiring, coaching, and retaining strong teams, and of communicating clearly with engineers, customers, executives, and investors
• Based in or near Los Angeles (strongly preferred), where most of the technical team and leadership are located

First-Year Roadmap

• 30 days: Learn the business, customers, architecture, and team. Assess the major risks and opportunities, and clarify ownership across engineering, QA, support, and incidents.
• 60 days: Align with Product on decision rights and cadence. Present a sequenced technical strategy covering scale, resilience, data normalization, and AI. Set baselines for quality, security, and cloud cost.
• 90 days: Launch the highest-value platform and data initiatives with clear owners and metrics. Tighten CI/CD and quality gates. Deliver a 12-month org and hiring plan.
• 6 months: Show measurable gains in availability, latency, MTTR, and cost per transaction. Put a governed data foundation into production use.
• 12 months: Launch a differentiated, monetizable data or intelligence product. Deliver an investor- and enterprise-ready technical package. Deploy automation that reduces manual work on integration failures.