Twilio

Software Engineer

Rol remoto de Software Engineering con fit claro de ubicación del candidato.

Publicado22 jul 2026

Países elegibles2 países aceptados

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

IrlandaEstados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

Architect and implement next-generation distributed systems capable of handling the immense throughput and concurrency requirements of Twilio Voice.
Design low-latency, high-scale APIs that empower customers with real-time access to their data and communications infrastructure.
Optimize and manage distributed database environments, ensuring high availability and performance across high-volume data stores.
Own the full development lifecycle, from initial system design and prototyping to the continuous operation of 24x7 production services.
Collaborate across engineering teams to solve "hard" distributed systems problems, ensuring our API layer is both resilient and developer-friendly.

A Master’s or Bachelor's degree and 5 + years of experience in software engineering, with a focus on backend or infrastructure systems.
Expertise in Distributed Systems: A deep understanding of consistency models, partition tolerance, and the challenges of scaling stateful services.
Core Languages: Proficiency in Java,Spring, Dropwizard and a strong grasp of building RESTful APIs at scale.
Database Fundamentals: Practical experience working with and tuning PostgreSQL, Aurora or similar relational databases.
Cloud Infrastructure: Familiarity with deploying and managing large-scale services on AWS or GCP.
Operational Excellence: Comfortable operating in an agile environment with a "you build it, you run it" mentality.

OLAP & Big Data: Experience with ClickHouse or other column-oriented databases for high-performance analytical queries.
Infrastructure as a code: Familiarity with tools such as Terraform, Harness for managing systems
Data Pipelines: Prior exposure to technologies like Kafka or Spark for moving and processing data between distributed systems.

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