What You’ll Accomplish
- Build and enhance high-performance, user-friendly frontend applications that power our customer-facing messaging products.
- Collaborate with Product and Design to create seamless experiences while maintaining code quality and avoiding tech debt.
- Take ownership of frontend scalability, reliability, and performance, ensuring fast and accessible applications.
- Proactively prevent regressions through robust testing and monitoring strategies.
- Continuously improve architecture by advocating for best practices in reusability, state management, and maintainability.
Your Expertise
- 5+ years of professional experience in frontend engineering with experience in modern frameworks. Recent experience with React is strongly preferred.
- Hands-on experience with GraphQL and schema design.
- A strong grasp of UX and web accessibility. Should be able to translate a design into high-quality interfaces.
- A proven track record of building applications that maintain a high bar of quality, and experience monitoring client-facing applications with tools like Datadog RUM.
- Solid understanding of software development best practices, including code reviews, writing unit and E2E tests, and continuous integration.
- Proven ability to collaborate effectively with cross-functional teams.
Nice to Haves
- Familiar with visual design systems and how they apply to UI component design
- Experience with optimizing frontend build systems
- Experience with large scale refactors or breaking version upgrades
- A preference for using code automations like codemods, ESLint (autofix) or LLM coding assistants
- Knowledge of backend software engineering including services-oriented architecture, distributed systems, AWS services and Kubernetes.
- Proficiency in Java, Kotlin, or Python, with a strong understanding of object-oriented programming.
What We Use
- Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, NX, and Playwright.
- Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
- Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS. Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm.
- Our machine learning is driven by custom and open source machine learning models, lots of data and built with Python, Anyscale, Tecton, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.
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