Lead Software Engineer – Payments

This is a fully remote position, open to applicants in United States.

📋 Description

• Take full responsibility for the technical health and quality of the Payments Platform, including architecture choices, sprint methodologies, release cycles, and release quality assurance.

• Establish team standards for specification-driven development and AI-assisted delivery; proactively enhance specifications and practices when AI-generated outputs do not meet quality expectations.

• Lead architectural decisions related to the API gateway and authentication, EventBridge/FundraisingBus event infrastructure, webhooks, and Reporting & Reconciliation.

• Ensure that API and event schemas are developed for durability, extensibility, and idempotency, adhering to financial-grade accuracy standards.

• Collaborate with the Platform Director on technical sequencing and the delivery of the roadmap.

• Work together with leads in Online Contribution and Corporate Giving to identify cross-domain integration points.

• Design and implement automated agents to streamline repetitive platform engineering workflows, minimizing manual effort for the team.

• Guarantee that team knowledge is organized, up-to-date, and consolidated, enabling agents and engineers to function without confusion.

• Provide mentorship to engineers on the platform team and participate in the interview and candidate assessment process.

• Eliminate systemic sources of friction in build, testing, deployment, and integration processes that hinder AI-assisted delivery.

⛳️ Requirements

• A minimum of 7 years of software engineering experience, including at least 2 years in a lead or technical leadership position.

• In-depth knowledge of payments systems and event-driven architecture; experience with payment provider integrations, particularly with Stripe, is highly preferred.

• Proficient in TypeScript and Node.js in a production environment; familiarity with AWS serverless infrastructure (such as Lambda, SQS, EventBridge, Aurora Serverless, or equivalents).

• Understanding of financial correctness criteria, including idempotency, duplicate detection, reconciliation, and handling of partial failures.

• Possess an AI-first mindset: actively utilize AI coding tools, create specifications that facilitate AI-generated code, and assess AI outputs for accuracy and technical debt.

• Proven history of managing end-to-end delivery quality for a platform or product segment.

• Excellent communication and collaboration skills across product and engineering teams.

• A strong commitment to leveraging technology to empower the social good sector.

🏝️ Benefits

• A comprehensive benefits package that promotes health, well-being, and professional growth.

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