Top Tech Jobs & Startup Jobs

Build and scale AI/ML solutions for healthcare revenue cycle automation. The role owns AI outcomes, identifies high-value use cases, shapes technical and product roadmaps, converts prototypes into scalable production systems, and architects infrastructure for training, testing, monitoring, security, and deployment. The engineer will apply ML, NLP, and LLM approaches to claims and workflow optimization while balancing technical tradeoffs, business value, cost, and operational efficiency.

Provide Level 1 customer support for healthcare billing platform inquiries, including claims processing, product functionality, bugs, and feature feedback. Collaborate with Product, Engineering, Operations, and Billing teams to resolve issues, escalate technical tickets, and meet SLAs. Create SOPs, macros, and help-center content while improving support workflows, quality, and cross-functional processes.

Lead cross-functional technical programs from planning through launch, translating implementation needs into technical requirements and milestones. Coordinate Engineering, Product, Design, and Operations teams, manage dependencies and risks, track KPIs, and communicate program status to leadership. The role requires technical fluency with APIs, databases, and cloud infrastructure, plus strong stakeholder management and experience working in fast-paced SaaS environments.

Manage and automate internal IT infrastructure as a product: scale onboarding/offboarding, migrate and maintain Apple MDM (Jamf/Kandji), build Zero-Touch Enrollment and JIT access automations, enforce zero-trust (SSO/SAML/MFA), troubleshoot macOS endpoints, and collaborate with Engineering, Security, and People Ops to improve security and operational workflows.

Join a structured accelerated sales program to learn healthcare revenue cycle management and enterprise sales. You will partner with senior account executives, qualify and close complex healthcare provider deals, build relationships with senior stakeholders, develop outcomes-driven business cases with Solutions Consultants, and contribute field insights to product, delivery, and go-to-market strategy. The role offers a path toward independently owning high-value enterprise deals.

Build and scale the company’s technical sourcing function from the ground up. Responsibilities include defining sourcing strategy and metrics, implementing AI-powered sourcing and automation workflows, leading technical intake sessions, developing employer branding and event strategies, and executing personalized candidate outreach. The role owns sourcing funnels, optimizes conversion rates, builds passive talent pipelines, and reports strategic outcomes to leadership.

Lead full-cycle recruiting for software engineering and leadership roles, including sourcing, screening, interviewing, offers, and candidate experience. Partner with hiring managers and senior leadership to develop talent strategies, build pipelines, optimize recruiting processes, and improve hiring outcomes. Use recruiting systems and metrics to increase productivity and inform hiring decisions. The role is primarily in person, with four days weekly in an office in San Francisco, New York, or Denver and one remote day.

Own product vision and execution in partnership with Engineering, Design, customers, and leadership. Improve product management practices, identify product and business opportunities, prioritize user needs, and build data-driven dashboards for accountability. Lead customer and internal communications for feature rollouts while remaining accountable for business outcomes. The role focuses on data-intensive healthcare payment software and requires technical fluency, collaboration, and outcome-oriented decision-making.

The Analytics Engineer will build data models and pipelines for reporting and analytics, improving data infrastructure for ML and AI products, and setting processes for data collection and analysis.

The Engineering Leader will oversee infrastructure and platform teams, managing projects, mentoring engineers, and defining technical strategies for scalable systems.