Software Engineer - Video

Twilio Twilio · Enterprise · United States · Remote · Engineering

Software Engineer role focused on Twilio's Voice Trust team, ensuring reliable voice communication for customers. The role involves full software development lifecycle participation, including design, implementation, testing, deployment, and on-call support for real-time, high-throughput, low-latency services. While the role is not primarily AI development, it requires significant interaction with AI tools, including evaluating AI-generated code and using AI coding assistants.

What you'd actually do

  1. Design and implement real-time services with high throughput and low latency requirements, verify, deploy and operationalize them
  2. Work closely with stakeholders to understand customer needs and, devise and deliver, simple, robust and scalable solutions
  3. Be comfortable expressing thoughts and ideas as detailed prose and use it as an effective means to collaborate with leads, architects and cross functional teams
  4. Embrace the challenge of scaling a complex distributed platform with points of presence globally, each one concerned with high availability, high reliability, high throughput, low latency, and media fidelity
  5. Figure out novel ways of solving customer problems for the Voice channel

Skills

Required

  • JVM based technologies
  • RESTful services
  • API design
  • event-driven architectures
  • Kafka
  • SQS
  • CI/CD pipelines
  • AWS
  • GCP
  • OpenStack
  • Azure
  • on-call rotations
  • incident response
  • monitoring/alerting tools
  • Prometheus
  • Datadog
  • Grafana
  • written communication skills
  • AI prompting
  • technical documentation
  • AI-generated code evaluation
  • Java fundamentals
  • code architecture
  • code review
  • code debugging
  • AI coding assistants
  • Computer Science fundamentals
  • data structures
  • algorithms
  • operating systems
  • distributed systems

Nice to have

  • AI productivity metrics
  • scaling data tiers
  • SQL
  • NoSQL database
  • caching technologies
  • scaling production backend systems
  • horizontally-scalable systems
  • resilient systems
  • performance under load
  • SIP protocol
  • Stir/Shaken protocol

What the JD emphasized

  • Minimum 2-3+ years of hands-on experience in a large scale, distributed applications environment on JVM based technologies
  • Experience building RESTful services, API design and event-driven architectures (Kafka, SQS)
  • Hands on experience with cloud infrastructures such as AWS, GCP, OpenStack or Azure
  • Experience with on-call rotations, incident response, monitoring/alerting tools (Prometheus, Datadog, Grafana)
  • Excellent written communication skills - essential for effective AI prompting and for creating clear technical documentation (with or without AI assistance)
  • Proven ability to critically evaluate AI-generated code for correctness, security, performance, and maintainability
  • Strong Java fundamentals with the ability to architect, review, and debug code whether written by you, teammates, or AI agents
  • Demonstrated proficiency working with AI coding assistants (Claude, GitHub Copilot, Cursor, or similar) - you should be able to describe your workflows and show examples