Quality Automation Architect

Company Description

At PayNearMe, we’re on a mission to make paying and getting paid as simple as possible. We build innovative technology that transforms the way businesses and their customers experience payments. Our industry-leading platform, PayXM™, is the first of its kind—designed to manage the entire payment experience from start to finish. Every click, swipe or tap is seamless, fast and secure, helping non-commerce businesses boost customer satisfaction, accelerate payments, and reduce costs.

Our single platform handles it all: cards, ACH, digital wallets such as PayPal, Venmo, Cash App Pay, Apple Pay and Google Pay, and even cash at more than 62,000 retail locations nationwide. Today, thousands of businesses across consumer lending, iGaming and online sports betting, property management, and tolling trust PayNearMe to deliver a payment experience that drives real results.

In September 2025, we raised a $50 million Series E funding round to accelerate our growth.

We’re a team of 300+ employees across 41 states, headquartered in Silicon Valley with satellite offices in Dallas, TX and Holmdel, NJ.

Join us and be part of a team that’s shaping the future of payments—one experience at a time.

Responsibilities:

We are establishing the role of Quality Automation Architect to lead the modernization of our software quality management practices, tooling, and mindset. As a payment processor and licensed money transmitter, PayNearMe operates in a regulated, high-stakes environment with a high bar for quality. We're investing heavily in agentic AI workflows that will substantially accelerate how quickly we produce code — and we need our ability to validate that code to scale at the same pace. Your primary objective will be to drive our transformation to a fully automated test suite and deployment pipeline while maintaining our current extremely high quality metrics.

Today, our approach to QA follows a traditional release-validation process, combining automated tests with manual scenarios and post-release smoke testing. As agentic AI accelerates our ability to deliver software, we need to transform the way we think about signals that give us confidence in production readiness. This role is about enabling teams to ship faster and with less friction, while honoring the trust placed in us by our clients and their customers by maintaining a high bar for correctness.

Success in this role requires both technical depth and an ability to work cross-functionally. You will need to both learn and teach, be an agent and driver of change, work within regulatory and compliance frameworks, and get buy-in for transformational initiatives across a diverse product development organization.

Software Quality Strategy

Define and lead the technical approach for modernizing software quality across our engineering organization, evolving from QA-as-gatekeeper toward a shared ownership model

Assess our current QA processes, test automation, manual testing practices, release validation, and tooling, then develop a practical roadmap for reaching successive levels of maturity

Propose and implement tooling, workflows and practices for building quality into the agentic SDLC

Establish a long-term vision for quality management that reduces handoffs and allows development pods to operate with autonomy

Partner closely with proddev leadership, SGRC, QA, and performance testing teams to align quality management practices with business risk, regulatory needs, and delivery goals

Define, track, and report the metrics that will shape decisions, such as coverage and defect escape rates

Test Architecture Automation

Define a modern test pyramid with clear definitions, ownership, and goals for unit, integration, contract, end-to-end, exploratory, and production validation layers, along with specialized considerations such as performance and security

Improve the reliability, speed, maintainability, and signal quality of our automated test suites; guide appropriate use of existing tools while identifying opportunities to improve, replace, or supplement them

Develop strategies for test data management (seed, synthetic, and production-like sets), environment reliability, contract testing, service virtualization, synthetic monitoring, and automated smoke testing

Identify opportunities to leverage agentic AI in test generation scenario discovery, and design workflows and skills for multi-agent analysis of generated code

Release Readiness

Design quality gates that are risk-based, automated where possible, and integrated into CI/CD pipelines

Improve sandbox and production smoke testing so that post-deploy validation becomes faster, more automated, and more reliable, supporting a fast-rollback strategy when needed

Collaborate with teams to define what “ready to release” means for different types of changes, services, and risk profiles

Mentorship and Change Leadership

Provide technical mentorship to QA engineers, software engineers, and en…