Block

Senior Software Engineer, Product Platform

Remote 10402 Engineering - Product Platform Engineering role with clear candidate location fit.

PostedRecently added

Eligible countries2 accepted countries

Seniority signalSenior

Work settingRemote

Accepted candidate locations

CanadaUSA

Role overview

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Design, build, and operate platform systems that help Block engineers ship software with more confidence and speed.
Work across areas such as deployment orchestration, CI/CD, Kubernetes, event streaming, databases, internal developer platforms, and reliability tooling.
Partner with engineering teams to understand their workflows, identify platform gaps, and deliver pragmatic solutions.
Help unify and modernize existing platforms while creating new ones where the business needs a stronger foundation.
Use AI tools to accelerate development, improve system understanding, prototype ideas, and raise the quality of engineering output.
Lead technical projects from problem framing through implementation, rollout, and operational ownership.
Make thoughtful tradeoffs between speed, reliability, maintainability, and long-term platform direction.
Contribute to an engineering culture that values curiosity, direct communication, early ownership, and learning through shipping.

A minimum of 5 years of related experience with a Bachelor's degree; or 3 years and a Master's degree; or equivalent work experience.
Experience building, operating, or improving backend or infrastructure systems used by engineering teams.
Strong software engineering fundamentals and the ability to work across unfamiliar systems, codebases, and technical domains.
Experience in one or more platform areas such as deployment systems, CI/CD, Kubernetes, Kafka or event streaming, Temporal, databases, observability, service infrastructure, or developer tooling.
A track record of turning ambiguous technical problems into clear plans and working solutions.
Comfort partnering with engineers and technical leaders across teams to understand needs, explain tradeoffs, and drive decisions.
Interest in using AI as part of your engineering workflow and helping others learn how to apply it well.
Curiosity, judgment, and willingness to ask questions early so the team can move with clarity.

Kubernetes, service infrastructure, deployment orchestration, CI/CD systems, Kafka and event streaming, databases, observability tooling, internal developer platforms, Go, Java, Ruby, and AI-assisted engineering tools.

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