Full Stack Engineer

🕒 Abril 10

🌐 Estados Unidos, Canadá – Remoto

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🏄 California – Remoto

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⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

🦅 Patrocina Visto H1B

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👻 Score fantasma 46%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Logo of Accelerant

Accelerant

201 - 500 funcionários

Fundada em 2018

🛡️ Seguros

☁️ SaaS

🤝 B2B

💰 $150.000.000 Private Equity Round - Accelerant em 2023-06

Insurance • SaaS • B2B

A Accelerant é uma plataforma de troca de risco e seguro digital que conecta agentes gerais gestores (MGAs), subscritores, resseguradores e capital institucional por meio de um mercado orientado por tecnologia e dados. A plataforma fornece análises em tempo real, ferramentas de subscrição, métricas de desempenho e suporte operacional (atuarial, de sinistros, regulatório) para agilizar a distribuição de seguros especializados e permitir uma implantação de capital mais rápida e transparente. A Accelerant se posiciona como uma parceira estilo SaaS para empresas de seguros especializados, concentrando-se em melhorar a eficiência, transparência e crescimento lucrativo.

Descrição

• Working closely with peer engineers, product managers, and other stakeholders to understand project requirements and deliver solutions that meet business needs. • Developing new frontend and backend features that help make our customers successful. • Writing backend code in Typescript that is fully unit tested. • Writing frontend code in Svelte, optimizing the frontend codebase for speed, efficiency, maintainability, and scalability. • Moving fast, while taking the time to ship high-quality code.

🎯 Requisitos

• Experience building and scaling web applications. • Strong understanding of modern JavaScript frameworks. • Strong coding ability. • Passionate problem-solving mindset. • Reputation for getting things done. • Strong sense of ownership. • Desire to learn and grow. • Experience with Typescript. • Experience with Svelte, web components, or equivalent component model. • Experience with cloud platforms such as AWS, and databases such as Postgres and Snowflake. • Experience with SQL-Like databases and data caching strategies such as Postgres, Snowflake, and Redis. • Experience integrating AI into the development lifecycle, including hands-on use of tools such as Cursor, Claude, and other LLM-based coding assistants to accelerate design, implementation, testing, and refactoring. • Experience building AI-enabled features and applications, including working with modern LLM APIs, prompt design, retrieval-augmented generation (RAG), vector databases, and developer tooling such as LangChain or equivalent frameworks.

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