• Create, develop, deploy, and maintain Tilled services • Design and implement highly reliable, fault tolerant systems • Collect and visualize detailed telemetry data to continuously improve systems • Advance and adhere to high-quality coding practices – unit testing, pair programming • End-to-end responsibility – continuously monitor and improve the services you create • Promote an engineering team culture that is always learning, motivated and collaborative • Work with a variety of technologies – Typescript, Angular, NodeJS, Postgres

• Projetar e desenvolver plugins do Twilio Flex em React e TypeScript, entregando experiências sob medida para agentes de contact center • Implementar fluxos no Twilio Studio para URA, SMS, WhatsApp e automações de e-mail • Desenvolver e manter Twilio Functions (serverless), configurações do TaskRouter e APIs do Conversations • Integrar Twilio Voice e Messaging às plataformas de CRM e ticketing dos clientes (ex.: Salesforce, HubSpot, Zendesk)

• Design, build, and operate the ingestion frameworks that pull data from operational databases, vendor APIs, document streams, and third-party feeds into Snowflake, Iceberg, and Databricks • Own and evolve the ingestion stack (AWS DMS, MWAA / Airflow, Fivetran) and design new patterns for API sources • Build self-service tooling so product engineers can onboard new sources without becoming experts in our infrastructure • Write and review the Terraform behind our ingestion infrastructure • Partner with product, data, and analytics teams to pick the right ingestion pattern for each source and stand it up end-to-end • Lead production troubleshooting and incident response, and turn each incident into a durable platform fix • Raise the bar on engineering quality, observability, cost discipline, and security in everything the team ships • Mentor mid-career engineers and pull peers along through code review, pairing, and design feedback

• Ownership of the full software development life cycle. • Work with cloud base architecture focusing on scalability and performance. • Address data challenges by implementing robust data engineering practices. • Code quality reviews and team collaboration. • Adopt a customer-first approach: Maintain a strong focus on customer needs and be relentless about delivering value.