VP, Platform Engineering at Happen in San Francisco, CA

Job description

Current Employees of Happen Bank: Please apply via your internal Workday Account Happen Bank (formerly LendingClub) is built around a simple purpose: to clear the way to help people turn intention into action, and action into financial progress. That means offering focused products, a frictionless mobile-first experience, and clear terms with no gotchas. Respect and fairness is part of our DNA, and that ideal shapes how we work, how we treat each other, and how we invest in our employees and our community. Join us in using data, bold thinking, and a commitment to innovation to help clear the way for millions of Americans to achieve more. About the Role The VP, Platform Engineering is the senior-most leader of Platform Engineering at Happen Bank, responsible for the strategy, roadmap, and execution of the foundational platforms that enable product engineering teams across the company. This leader owns AI Infrastructure, DevOps and software delivery, Change Management, enterprise Testing, Database Administration, and Incident Management & Observability. You’ll bring deep technical expertise and executive leadership to build the platforms, guardrails, and services that enable Engineering teams to move quickly, safely, and reliably. A key focus will be defining Happen Bank’s multi-year AI Infrastructure strategy—including model and platform selection, build-versus-buy decisions, client-facing AI capabilities, governance, and shared tooling—while advancing software delivery, quality, database reliability, and production resilience across the technology organization. You’ll partner across Technology and Product Engineering to align platform investments with the broader technology, product, and AI modernization agenda, building a high-performing organization grounded in the belief that speed, quality, and safety are all requirements. What You'll Do AI Infrastructure Vision & Strategy Own the enterprise vision, strategy, and roadmap for AI Infrastructure, including evaluation and selection of AI/LLM models and platforms and a clear point of view on which capabilities to build in-house versus consume as a service Lead the development of client-facing AI technologies, gateways, and shared tooling that enable product teams to safely and efficiently integrate AI capabilities into customer experiences Establish standards for model governance, cost management, latency, security, safety, and scalability as AI adoption grows across the engineering organization Developer Platform, DevOps & Software Delivery Define the strategy and standards for CI/CD, developer tooling, infrastructure as code, automated deployment, and environment management to measurably improve engineering velocity and reliability Own the roadmap for build and release capabilities, ensuring tooling and processes scale with engineering headcount, product surface area, and technical complexity Establish and continuously evolve Change Management guardrails, release controls, testing expectations, sign-offs, rollback plans, and monitoring standards that enable teams to ship quickly while protecting customer experience and production stability Use incident and defect data to continuously improve software delivery and Change Management practices, balancing delivery speed, quality, and risk Enterprise Testing & Quality Own the enterprise testing strategy and shared testing capabilities across Software Engineering, Data, and other technology teams Define quality standards, testing expectations, and SLAs that establish clear release-readiness requirements across Product and Platform Engineering Advance AI-enabled testing practices, including automation, self-healing tests, and AI-assisted test generation, to improve coverage and efficiency while reducing manual QA effort Database Administration Lead the Database Administration function, establishing a clear charter, priorities, and service expectations for Engineering and the broader organization Ensure the DBA organization delivers