Full-Stack Software Engineer II: AI-Driven Inventory

CarGurus Early Careers

Boston (MA)

Hybride

USD 112 000 - 141 000

Plein temps

14 jours+
Générateur de candidature

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Avantages offerts par ce poste

Daily lunch
Car discount
Wellness apps
Commuting covered
Generous time off

Résumé du poste

CarGurus is seeking a Software Engineer II (Full Stack) to advance inventory products for dealers. You will transform market data into engaging features, building brand-new dealer-facing tools across the stack.

Expect cross-functional collaboration with data scientists and product managers to guide projects from concept to design, implementation, testing, and performance measurement. You will contribute code that emphasizes scalability and maintainability, while exploring AI-assisted tooling to

Qualifications

  • 2-5 years of hands-on software development experience.
  • Proficiency in React and Javascript fundamentals.
  • Proficiency in Java and SQL.
  • Experience with AI coding tools is a plus.
  • Knowledge of distributed systems and microservice patterns.
  • Strong understanding of data structures, algorithms, and complexity.

Responsabilités

  • Develop and deploy clean, well-tested code with high quality.
  • Provide support and improvements to core systems for internal teams.
  • Integrate modern AI tools into the development pipeline to boost productivity.
  • Collaborate with data scientists and product managers from concept to delivery.

Connaissances

React
Javascript
Java
SQL
AI tools
Distributed systems
Algorithms
Data structures
Rapid iteration

Outils

None

Description du poste

CarGurus is seeking a Software Engineer II (Full Stack) to advance inventory products for dealers. You will transform market data into engaging features, building brand-new dealer-facing tools across the stack.

Expect cross-functional collaboration with data scientists and product managers to guide projects from concept to design, implementation, testing, and performance measurement. You will contribute code that emphasizes scalability and maintainability, while exploring AI-assisted tooling to

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