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# Software Engineer, Fleet Management

- **Company:** Tesla Motors
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Algorithm Design, Automated Storage and Retrieval Systems, Data Structures, Distributed Systems, Firmware, Job Scheduling, Uptime, Motion Planning, MySQL, Routing, Site Reliability Engineering Practices, Software Engineering, SQL Databases, Systems Architecture, Systems Integration, Data Logging, Multi-Agent Systems, State Machines, Backend, Event Driven Architecture, Kubernetes, Infrastructure Automation Frameworks, Apache Kafka, Graphql, Front End Software Development, Multiaccess Edge Computing, Grpc, Docker, Microservices
- **Published:** October 15, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/86899114/1

## About the Role

* 3+ years of software engineering experience with strong foundations in algorithms, data structures, and systems design

 * Deep interest or experience in robotics, multi-agent systems, fleet management,logisticsoptimization, or operations research - you can reason about graph algorithms, optimization problems, and state machines

 * Strongproficiencyin Go; working familiarity with the broader stack:GraphQL,gRPC, NATS or Kafka, SQL (MySQL), Docker, and Kubernetes

 * Comfortable working with distributed systems concepts: real-time messaging, event-driven architectures, state management, and eventual consistency

 * Product-minded - you think about the user's experience, not just the engineering solution, and consider how factory operators and engineers will interact with what you build

 * Experience building user-facing features, SRE practices, CI/CD pipelines, or infrastructure automation is a plus - the team owns its full stack and build tooling end-to-end

 * Experience with fleet management, warehouse automation, industrial automation systems, robotics controls, or hardware-software integration is a plus

## Description

Tesla builds fleet management and robot control software that orchestrates autonomous robots and automation systems - including AMRs, ASRS and conveyance systems - across global manufacturing and warehouse facilities. The platform integrates with robots, industrial equipment, and internal MES systems to coordinate material flow end-to-end. These systems are production-critical and directlyimpactfactory throughput, uptime, and scalability., We are seeking a Software Engineer to join the Fleet Management team. The Fleet Management domain handles job scheduling, vehicle routing, traffic management, conflict resolution, and fleet coordination at scale - a distributed, event-driven system spanning microservices, real-time messaging, and edge computing. This is a full stack role with a strong backend emphasis - you will spend the majority of your time on scheduling, routing, and orchestration algorithms in Go, while also exploring AI-driven approaches to optimization, contributing to frontend tooling, and occasionally stepping into robotics controls work alongside the firmware team.

You will work within a small, focused team alongside a Staff-level domainleadand experienced engineers. You will receive mentorship on algorithm design and systems architecture while being expected to take ownership of meaningful features from day one.

This position is based in Austin, TX (onsite).
What You'll Do

 * Implement and improve job scheduling, vehicle routing, traffic management, and fleet orchestration algorithms in Go - including task assignment, path planning, conflict resolution, dynamic replanning, and resource allocation

 * Explore and apply AI and ML techniques to improve scheduling, routing, anomaly detection, and operational decision-making

 * Build andmaintainintegrations with industrial equipment, MES systems, and other internal platforms that connect fleet management to the broader factory automation stack

 * Contribute to frontend tooling that gives factory operators real-time visibility into fleet status, scheduling decisions, and system health

 * Write comprehensive tests for algorithmic correctness, edge cases, and performance

 * Design and improve observability: metrics, logging, tracing, and dashboards that make fleet behavior transparent anddebuggable

 * Collaborate with firmware engineers to ensure fleet-level decisions translate to correct vehicle behavior, and contribute to robot control software when needed