Senior Software Engineer

Twilio is shaping the future of communications with innovative solutions for businesses and developers worldwide. The Senior Software Engineer will be part of the Voice & Video Postflight team, focusing on building and evolving distributed systems and APIs to support Twilio's Voice capabilities.

Responsibilities:

• 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

Requirements:

• A Master's or Bachelor's degree and 5 + years of experience in software engineering, with a focus on backend or infrastructure systems or equivalent combination of years of experience
• 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