Staff Software Engineer (l4)

Twilio Twilio · Enterprise · ON · Remote · IT

Staff Software Engineer for Twilio's Enterprise AI Engineering team, focusing on building production-grade, full-stack AI applications and agentic solutions for customer support and other business functions. The role involves technical leadership, full-stack development (React, JavaScript/TypeScript), distributed systems, and mentoring engineers, bridging AI research with production systems.

What you'd actually do

  1. Co-lead the design and development of our software infrastructure, driving technical vision and strategy to ensure scalability, reliability, and performance.
  2. Drive the development of sophisticated, stateful web applications. You will oversee the integration of complex React-based front-ends with backend modular services, ensuring a seamless UI experience.
  3. Serve as developer leader in distributed systems, data technologies, with strong software engineering skills.
  4. Drive technical innovation and research to stay at the forefront of emerging data technologies and best practices.
  5. Mentor and elevate a team of high-performing engineers. You don’t just write great code; you foster a culture of technical excellence, helping senior and mid-level engineers level up through deep-dive code reviews and architectural workshops.

Skills

Required

  • 8+ years of experience in data engineering, software development, or a related field
  • at least 3 years in a technical leadership role
  • Experience with full-stack development building web apps
  • modern programming languages such as JavaScript, Typescript or React
  • architecting and delivering complex data projects at scale
  • deep understanding of data infrastructure and distributed systems
  • data modeling
  • data warehousing
  • ETL processes
  • designing and optimizing data pipelines
  • Excellent communication and collaboration skills
  • Strong leadership skills
  • mentoring and developing high-performing engineering teams
  • Demonstrated ability to thrive in a fast-paced, dynamic environment and deliver results under tight timelines

Nice to have

  • Experience developing production-quality LLM applications
  • using modern agent frameworks such as Langchain, Langgraph, Llamaindex, LangSmith, LangFuse, CrewAI, and/or others
  • Expertise in big data technologies such as Hadoop, Spark, Kafka
  • cloud-based data services (AWS/GCP/Azure)

What the JD emphasized

  • building production grade, full-stack AI applications
  • engineering the entire lifecycle of agentic applications

Other signals

  • building production grade, full-stack AI applications
  • engineering the entire lifecycle of agentic applications
  • bridge the gap between bleeding-edge AI research and robust, full-stack production systems