VP, Platform Engineering

LendingClub•San Francisco, CA

4d•$260,000 - $290,000•Hybrid

About The Position

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.

Requirements

13+ years of progressive software engineering, DevOps, platform engineering, or related technology experience, including significant experience leading complex engineering organizations
Bachelor's degree or higher, or equivalent combination of education and experience
10+ years in a senior engineering leadership role leading multiple technical domains and managers of managers, with experience across AI Infrastructure, DevOps, Testing, DBA, Observability, or related platform functions
Demonstrated experience setting AI Infrastructure strategy, including evaluating and selecting AI/LLM models and platforms and building client-facing AI gateways, tooling, or capabilities in production environments
Deep technical fluency across DevOps pipelines, testing harnesses and automation, API and contract design, database architecture, and observability, with the ability to go deep with technical teams while operating at an executive and strategic level
Track record of building and maturing observability practices, SLA/SLO frameworks, and incident management processes at scale, with a high bar for operational excellence and root-cause analysis
Experience leading or partnering closely with Database Administration functions, with a clear perspective on how DBA teams can deliver high-leverage value to Engineering
Experience building enterprise testing strategies and shared testing capabilities, with a focus on automation and AI-enabled testing efficiency
Practical experience building platforms and shared services across modern distributed technology environments, including Java, Scala, and/or Node.js; databases such as Postgres, MySQL, Cassandra, or DynamoDB; and asynchronous messaging technologies such as SQS/SNS or Kafka
Strong executive presence and cross-functional influence with the ability to align platform investments with company, product, and technology strategy
Demonstrated success developing leaders and building leadership bench strength across complex, multi-domain engineering organizations
You build functions that evolve, embedding AI capabilities into how strategy is developed and executed. You create the systems and conditions for teams to challenge assumptions and deliver breakthroughs while maintaining a high standard for security, model governance, data integrity, responsible production deployment, and long-term maintainability

Nice To Haves

Experience in fintech or banking, particularly within Loan Originations, Servicing, or Banking Web and Mobile Applications

Responsibilities

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
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
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
Lead the Database Administration function, establishing a clear charter, priorities, and service expectations for Engineering and the broader organization
Ensure the DBA organization delivers high-leverage capabilities across performance tuning, schema design guidance, capacity planning, and data reliability
Partner with Engineering leaders to proactively identify and address database risks, scalability needs, and opportunities as the platform evolves
Own a robust incident management framework from detection and response through resolution and post-incident review, with a focus on minimizing customer impact and strengthening root-cause learning
Establish clear SLAs, SLOs, and operational expectations that provide real-time visibility into system health and enable teams to proactively identify and recover from degraded services
Strengthen the enterprise observability strategy and stack in partnership with Technology Operations, driving consistent instrumentation, alerting, dashboards, and operational standards across the technology environment
Set the strategy and multi-year roadmap across Platform Engineering, aligning investments and priorities with the broader product development and technology roadmap
Anticipate emerging platform needs and determine where Happen Bank should invest to improve engineering productivity, reliability, scalability, security, and innovation
Represent Platform Engineering in enterprise technology strategy, planning, and investment decisions, providing clear recommendations on priorities, tradeoffs, and resource allocation
Build, coach, and retain a high-performing leadership organization across AI Infrastructure, DevOps, Testing, DBA, and Observability, with a strong focus on talent development and leadership bench strength