Staff Software Engineer, Fleet Management
- Location
- Austin, TX · On-site
- Job type
- Full-time
- Level
- Lead / Staff
- Listed
- 29 days ago
About the role
Staff Software Engineer, Fleet Management | Tesla (Engineering & Information Technology)
Location: AUSTIN, Texas | Req ID: 267968 | Job Type: Full-time
What to Expect
Tesla’s Factory Automation Robotics team 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. These systems are production-critical and directly impact factory throughput, uptime, and scalability.
The Fleet Management domain is the algorithmic and systems core of this platform — a distributed, event-driven system spanning microservices, real-time messaging, and edge computing. It handles job scheduling, vehicle routing, traffic management, conflict resolution, and fleet coordination at scale.
We are seeking a Staff Software Engineer to lead the Fleet Management domain. You will own the technical direction, write production code, and lead a team of engineers while scaling the system to support more factories, more robots, and more complex material flows. The ideal candidate combines deep expertise in multi-agent scheduling or fleet coordination with hands-on distributed systems experience, strong product instincts, and an AI-forward mindset.
This position is based in Austin, TX.
What You'll Do
- Own the technical direction and algorithmic design for job scheduling, routing, traffic and resource management, and fleet orchestration
- Lead and grow a team of engineers: mentor on algorithm design and systems thinking, review technical approaches, and set the bar for quality and rigor
- Write production code in Go — this is a hands-on technical leadership role, not a management position
- Design and evolve scheduling algorithms that handle multi-robot coordination, deadlock avoidance, dynamic replanning, and priority-based dispatching
- Drive architectural decisions across the fleet management stack: Go, GraphQL, gRPC, NATS, Kafka, Temporal, MySQL, and Kubernetes
- Identify opportunities to apply SI and machine learning to scheduling, routing, anomaly detection, and operational decision-making
- Own the interface between fleet-level decisions and vehicle-level execution, working closely with the Firmware Controls team to ensure correctness under real-world conditions
- Partner with the Integration team to validate that algorithms perform reliably in live factory environments and feed production learnings back into system design
- Translate operational pain points and user needs into technical direction, driving the product toward measurable improvements in factory throughput and uptime
- Drive the technical roadmap for fleet management: scaling to new factories, reducing downtime, and improving scheduling efficiency
What You'll Bring
- 7+ years of software engineering experience, with 3+ years focused on multi-agent systems, fleet management, logistics optimization, or robotics coordination
- Deep expertise in at least two of: job scheduling algorithms, vehicle routing, traffic management, conflict resolution, resource allocation
- Demonstrated experience building and operating distributed systems in production - event-driven architectures, message brokers, service decomposition, and the operational realities of running them
- Strong proficiency in Go; working familiarity with the broader stack: GraphQL, gRPC, NATS or Kafka, SQL (MySQL), Temporal, Docker, Kubernetes, and Helm
- Experience shipping algorithmic systems into real production environments, not just research or simulation
- Track record of technical leadership: setting architectural direction, mentoring engineers, and driving technical decisions across teams
- Strong product sense with the ability to understand user pain, domain constraints, and independently drive toward a better product
- Experience with real-time or near-real-time decision systems - you understand latency, throughput, and reliability constraints
- An AI-forward mindset with a drive to incorporate AI-driven approaches into product development, whether that is ML for scheduling optimization, LLMs for operational tooling, or AI-assisted development workflows
- Background in warehouse automation (WMS/WES/WCS), AMR/AGV fleet management, or factory material flow is a plus
Benefits
Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
- Medical plans > plan options with $0 payroll deduction
- Family-building, fertility, adoption and surrogacy benefits
- Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
- Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA
- Healthcare and Dependent Care Flexible Spending Accounts (FSA)
- 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
- Company paid Basic Life, AD&D
- Short-term and long-term disability insurance (90 day waiting period)
- Employee Assistance Program
- Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
- Back-up childcare and parenting support resources
- Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
- Weight Loss and Tobacco Cessation Programs
- Tesla Babies program
- Commuter benefits
- Employee discounts and perks program
- Earned Wage Access: Real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr. Managers levels)
From Tesla's careers page, first listed on Rolev.ai on October 12, 2026. Rolev.ai is not the employer.
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Common questions
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This Staff Software Engineer, Fleet Management position at Tesla is located in Austin, TX (On-site). Always check Tesla's application page for specific state eligibility or relocation policies.
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