Full Stack Engineer

🕒 il y a 6 mois

🌐 États-Unis, Canada – Distant

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🏄 California – Distant

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⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

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👻 Score fantôme 46%

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🗣️🇺🇸🇬🇧 Anglais requis

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Logo of Accelerant

Accelerant

201 - 500 employés

Fondée en 2018

🛡️ Assurance

☁️ SaaS

🤝 B2B

💰 €150 000 000 Private Equity Round - Accelerant en 2023-06

Insurance • SaaS • B2B

Accelerant est une plateforme d'échange de risques et d'assurance numérique qui connecte les agents généraux gestionnaires (MGA), les souscripteurs, les réassureurs et le capital institutionnel à travers un marché basé sur la technologie et orienté vers les données. La plateforme fournit des analyses en temps réel, des outils de souscription, des mesures de performance et un support opérationnel (actuariat, réclamations, conformité réglementaire) pour rationaliser la distribution de l'assurance spécialisée et permettre un déploiement de capital plus rapide et transparent. Accelerant se positionne comme un partenaire de type SaaS pour les entreprises d'assurance spécialisée, visant à améliorer l'efficacité, la transparence et la croissance rentable.

Description

• 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.

🎯 Exigences

• 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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