Top Engineering Jobs in Austin, TX

As a Senior Software Engineer, you'll build systems for route planning, dispatch, and real-time tracking for various logistics and operations, improving dispatcher tools and user experiences.

The role involves building core infrastructure for orchestrating intelligent agents, defining platform primitives, and ensuring systems scale and reliability. Collaboration with internal teams and end-to-end system ownership are essential.

Design, develop, test, and operate cloud-connected vehicle firmware and services. Build and maintain firmware features in C/C++ and Go, support large-scale device fleets, implement observability and rollout metrics, triage customer and QA issues, and collaborate with product, firmware, and systems teams to deliver production-ready IoT solutions.

Lead design and delivery of scalable customer-facing features, services, and APIs that process real-time data and AI-powered insights. Build web experiences, contribute to LLM/AI workflows, ensure reliability through observability and rollout practices, and collaborate cross-functionally with Product, Design, ML, and platform teams.

The Senior Software Engineer will lead projects for the Forms platform, designing and building features across web, mobile, and backend systems while mentoring other engineers and improving platform scalability and reliability.

Design and build end-to-end web and AI-powered dashboard features, scale cross-platform full-stack infrastructure, standardize product patterns, mentor engineers, lead cross-team technical projects, and collaborate with product and design to improve user workflows and AI adoption.

Design, build, and operate scalable, secure data platform infrastructure for ingesting, processing, cataloging, and accessing petabytes of data. Improve Spark/Databricks reliability and developer experience, build ingestion/replication systems, develop internal libraries and tooling (Go/Python), and collaborate with cross-functional teams to support analytics, ML, and customer-facing data products.

Build automated reliability and self-healing platform tooling to protect production at scale. Improve incident management, reduce alert noise, evolve observability (monitoring, SLOs, performance detection), and develop AI-driven operational automation. Partner with product teams to diagnose reliability gaps, drive incident prevention, and champion operational excellence and best practices across engineering.