Senior Software Engineer

Welcome to the Agentic Commerce Era

At Commerce, our mission is to empower businesses to innovate, grow, and thrive with our open, AI-driven commerce ecosystem. As the parent company of Big Commerce, Feedonomics, and Makeswift, we connect the tools and systems that power growth, enabling businesses to unlock the full potential of their data, deliver seamless and personalized experiences across every channel, and adapt swiftly to an ever-changing market.

We believe in harnessing AI responsibly to unlock new possibilities, and we’re looking for individuals who use it intentionally to solve problems, accelerate outcomes, and expand what’s possible in their role. Our purpose is to help businesses confidently solve complex commerce challenges so they can build smarter, adapt faster, and grow on their own terms. If you want to be part of a team of bold builders, sharp thinkers, and technical trailblazers who shape the future of commerce, this is the place for you.

Location:

London / UK (Hybrid)

Company:
Commerce

Commerce is an open SaaS ecommerce platform that helps merchants build, run, and grow their businesses.

The Data Team builds systems that support merchant-facing products, integrations, analytics, reporting, and the infrastructure behind them.

We are looking for a Senior Software Engineer who can own complex problems from discovery through production.

This role is not narrowly frontend, backend, or data engineering. The right person can work across services, APIs, event flows, product experience, production debugging, and cross-team delivery.

They should be comfortable taking an unclear business or customer problem, breaking it down, making trade-offs clear, and shipping a reliable solution.

We need someone who raises the engineering bar without needing a lot of direction.

• Design and build reliable services, APIs, and product-facing workflows.
• Work across backend systems, UI surfaces, event processing, and third-party integrations.
• Turn unclear problems into concrete technical plans.
• Own production behavior, including monitoring, alerting, logging, debugging, and runbooks.
• Work with product, design, infrastructure, support, and other engineering teams.
• Improve quality through tests, code review, observability, and simpler designs.
• Use data and production evidence to validate decisions.
• Take ownership of incidents and production issues when systems do not behave as expected.

• Strong senior-level engineering judgment.
• Experience owning ambiguous technical work.
• Ability to solve problems across multiple layers of a system.
• Strong backend engineering experience with production services.
• Enough frontend experience to work on product‑facing workflows when needed.
• Comfort with distributed systems, event-driven flows, caching, retries, rate limits, and failure modes.
• Strong production debugging skills.
• Ability to explain trade-offs clearly.
• Bias toward simple, reliable solutions.
• Good communication during incidents, reviews, and cross-team work.

• 5+ years of software engineering experience.
• Strong experience with Java, Scala, Kotlin, Go, or a similar backend language.
• Experience building APIs, services, and integrations.
• Experience with SQL and data-backed product behavior.
• Experience with GCP, AWS, or another cloud platform.
• Experience with Kafka, RabbitMQ, Pub/Sub, or similar event systems.
• Experience with logs, metrics, dashboards, alerts, and tracing.
• Experience writing automated tests and reviewing code.

• React / Type Script or similar frontend experience.
• Experience with merchant-facing or customer-facing product workflows.
• Experience with third-party integrations, account linking, OAuth, or external APIs.
• Experience with Redis, caching, rate limiting, queues, or high-volume event processing.
• Experience with analytics, reporting, attribution, or event data products.

• Own the outcome, not only the ticket.
• Ask what problem we are solving before choosing the implementation.
• Prefer simple designs that other engineers can operate.
• Validate risky assumptions early.
• Use production data and customer…