Staff Software Engineer, Go-to-Market Systems & AI

Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together.

So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, offer buy now, pay later functionality, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale.

Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same.

The Role

The Go-to-Market Engineering team builds the systems, automations, and AI-powered experiences that help our sales teams spend less time on manual work and more time serving customers. As a Staff Software Engineer, you will be the technical owner of our go-to-market technology stack, setting its architecture and long-term direction while leading engineers through complex, high-impact sales problems. You will partner with Sales, Sales Strategy & Operations, Product, Data, and Engineering leaders to deliver reliable, scalable solutions that improve sales productivity and business performance.

You Will

• Own the technical strategy, architecture, and long-term evolution of our go-to-market technology stack.
• Design, build, and operate production-grade AI agents and automated workflows that reduce manual sales work, improve decision-making, and give time back to sales teams.
• Lead technical execution across initiatives of varying sizes by setting direction, breaking down complex problems, reviewing designs, and helping engineers deliver high-quality solutions.
• Remain hands-on throughout the software lifecycle, from prototyping and architecture through implementation, testing, deployment, and production operations.
• Partner with Sales and Sales Strategy & Operations to understand workflows, identify high-value opportunities, and translate business problems into scalable technical solutions.
• Establish the patterns, evaluation methods, and guardrails needed to build AI systems that are reliable, observable, secure, and safe to use with sensitive business data.
• Define success measures and use data, evaluations, and user feedback to improve the accuracy, adoption, and business impact of new capabilities.
• Make thoughtful build-versus-buy decisions and guide integrations across internal platforms, customer relationship management systems, data services, and third-party tools.
• Build alignment with senior technical and business partners, communicate complex tradeoffs clearly, and raise engineering standards through mentorship and design reviews.

You Have

• A minimum of 12 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or a PhD with 5 years experience; or equivalent experience.
• Experience setting technical direction and delivering complex, business-critical systems across multiple teams or functional areas.
• Experience designing, building, and operating production software that uses large language models, AI agents, tool calling, retrieval, workflow orchestration, or related technologies.
• A track record of moving AI capabilities from prototype to production, including evaluation, observability, security, reliability, and human oversight.
• An AI-native approach to engineering, using AI tools throughout development while applying sound judgment about when to use models, deterministic software, or human review.
• Strong software engineering and system-design skills, with the ability to work hands-on across application, service, integration, and data layers.
• Experience leading technical execution through influence, mentorship, architecture, and direct contribution, without relying o…