Top Tech Jobs & Startup Jobs

Build and maintain Mercury’s design system components, patterns, tokens, and foundations with strong accessibility, performance, and visual quality. Lead projects that improve product team velocity, advance prototyping workflows, and apply AI to design-system development. Mentor engineers and designers, establish best practices, and provide systems-oriented technical leadership across ambiguous, high-impact initiatives.

Lead fraud incident response across Mercury products, coordinating containment, impact assessment, communications, remediation, and postmortems. Prepare defensible reports for bank partners, auditors, regulators, and internal governance. Serve as an operational contact for partner banks, support audit and exam responses, track corrective actions, and improve fraud controls, procedures, training, reporting, and tooling. The role requires strong fraud investigation, regulatory financial-services, payment-rail, data interpretation, writing, and cross-functional influence experience.

Manage and mature Mercury’s enterprise-wide third-party risk management program as it prepares for bank-level regulatory expectations. Responsibilities include conducting risk assessments, rating third parties, overseeing first-line due diligence, tracking remediation, maintaining reporting and metrics, supporting audits and exams, implementing tooling and automation, and improving policies and lifecycle processes. The role requires cross-functional influence across Procurement, Finance, Information Security, Legal, Privacy, and Compliance.

Own Mercury’s recruiting systems, including ATS, sourcing, scheduling, interview intelligence, Workday integrations, and headcount planning tools. Lead vendor evaluations, system migrations, integrations, data mapping, cutovers, training, permissions, workflows, and troubleshooting. Build dependable AI recruiting workflows and maintain a searchable recruiting knowledge layer. Partner cross-functionally with IT, People Ops, Finance, and AI teams while helping recruiters adopt operational changes.

Owns the cross-functional GTM Engine program across Growth Product, Marketing, Revenue, and GTM Data. Responsibilities include integrated planning, dependency and risk management, decision facilitation, leadership reviews, operating-cycle design, launch readiness, dashboards, written updates, and automation. The role creates a shared system for customer data, attribution, campaign execution, and collaboration across GTM teams.

Lead corporate development across M&A, strategic investments, market intelligence, investor relations, fundraising, and post-close integration. Responsibilities include sourcing and evaluating targets, financial modeling, diligence, synergy analysis, executive and board materials, KPI reporting, investor updates, and cross-functional integration workstreams. The role partners with Product, Engineering, GTM, Finance, Legal, People, and executive leadership to shape strategic decisions and grow Mercury’s corporate development capabilities.

Own and build Mercury's enterprise partnerships motion by sourcing and closing platform-scale, embedded finance and API-driven distribution deals. Lead outreach to C-suite partners, architect bespoke integration and commercial structures, model deal economics, and coordinate cross-functional teams from negotiation through legal close, integration, and launch.

Owns Mercury’s new-hire onboarding, apprenticeship, and internship programs. Responsibilities include designing learning experiences, coordinating facilitators and cohorts, supporting managers and mentors, building AI-enabled systems and automation, analyzing feedback and data, and partnering with Recruiting, People Operations, and company leaders to improve emerging-talent programs.

Build and own machine-learning models for small-business lending, including transaction classification, forecasting, anomaly detection, and revenue estimation. Deploy production models with testing, monitoring, and documentation. Partner with Credit and Product on underwriting policy, lending decisions, pricing, repayment terms, and uncertainty quantification. Establish ML standards while transforming financial data into defensible assessments of business health.

Build and own machine learning models for small-business lending, including transaction classification, cash-flow detection, revenue estimation, forecasting, and anomaly detection. Deploy production-grade models with monitoring, observability, testing, and documentation. Partner with Credit and Product on underwriting policy, lending decisions, pricing, repayment terms, and uncertainty quantification. Establish technical standards for machine learning across the data science team.