Staff Full Stack Engineer, Payments Intelligence
On-siteSeattle, Washington, United States
Job Summary
Define technical strategy for multiple experiences across the Payment Intelligence portfolio, focusing on quality and performance. Champion a quality-first engineering culture by establishing standards, tooling, and processes that enable high-quality code at scale. Partner with large merchants to co-build payment-centric intelligence solutions while collaborating cross-functionally with product, design, and ML teams to ship robust software. Work across the full stack, contributing to infrastructure, foundational systems, frontend, API, and ML-adjacent tasks. This role requires 10+ years of experience, including 5+ in strategic leadership, and involves navigating ambiguity in a fast-moving organization to drive pragmatic solutions that accelerate business growth.
Required Qualifications
- 10+ years of software engineering experience
- 5+ years of experience in a strategic technical leadership role
- Experience leading engineering team(s) working on Distributed systems, API design, and user facing products
- Proven track record of delivering pragmatic solutions that accelerate business growth
- Ability to drive projects at a high-level while also being hands on and contributing directly to technical solutions as necessary
- Effective communication skills
- A proven ability to work cross-team, cross-org, and cross-functionally
Desired Qualifications
- Experience with payments systems and/or fraud detection
- Familiarity with ML systems in production: model serving, training pipelines, observability, and evaluation
- Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly
- Experience across a range of software languages and frameworks; our stack includes Java, Ruby, Python, TypeScript, Kafka, Flyte, Airflow, and Mongo
- Experience navigating ambiguity in a fast-moving organization - you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge
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