Staff Software Engineer - Platform Integration, Robot Software
Wayve · Sunnyvale, California USA
- Location
- Sunnyvale, California USA
- Salary
- $275K - $300K
- Funding
- $2.58B total
- Posted
- Oct 15, 2026
Wayve is hiring a Staff Software Engineer - Platform Integration, Robot Software based in Sunnyvale, California USA. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.
Apply directly at WayveRole details
Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. 🛠️ About our Engineering Teams Wayve is building embodied AI that can drive any vehicle, anywhere. Within Robot Software, the Platform Integration team brings together the software and interfaces that enable our AI Driver to operate on new development platforms. The team owns early vehicle software integration, drive-by-wire and the vehicle-facing software drivers. We work across software, hardware, controls and operations to bring up new vehicle variants, improve their reliability and establish repeatable processes for validation and handover. As a Staff Software Engineer, you’ll bring deep experience in software, hardware, robotics and autonomous vehicle integration. You’ll lead the team’s integration architecture, mentor engineers and help resolve its most complex technical challenges. You’ll work with the Engineering Manager on the technical roadmap and with other leads across Robot Software on system design and integration decisions, while staying hands-on with software development and vehicle bring-up. 🧠 Your day-to-day - Lead integration architecture and author design documents that define interfaces, evaluate trade-offs and guide implementation across vehicle programmes. - Partner with the Engineering Manager to shape the technical roadmap, balancing programme delivery with improvements to architecture, tooling and maintainability. - Unblock the most complex integration challenges, diagnosing problems across application software, middleware, operating systems, networks and hardware. - Mentor engineers through design discussions, code reviews and hands-on debugging, building the team’s technical judgement and independence. - Represent Platform Integration in technical discussions across Robot Software, aligning with other technical leads on interfaces, dependencies and ownership. - Develop and review production software, establishing patterns that reduce bespoke integration work and improve reuse. - Lead targeted bench, HiL and vehicle investigations where hands-on work is needed to resolve uncertainty or validate a design. - Turn lessons from bring-up and field issues into better diagnostics, integration practices, documentation and validation. 🧩 What you’ll be working on - Integration architecture for new vehicle programmes across embedded compute, sensors, vehicle interfaces, networks and software services. - Shared vehicle-facing components and abstractions that support multiple hardware configurations without duplicating integration logic. - System-level integration of Linux-based robotic and automotive platforms with multi-process and distributed architectures. - Sensor integration, calibration, synchronisation and data validation, working with the teams that own those capabilities. - Vehicle communication and control interfaces, including CAN, Automotive Ethernet and drive-by-wire systems. - Integration across automotive compute platforms such as NVIDIA DRIVE and Qualcomm Snapdragon Ride. - Bench, HiL and vehicle validation strategies that identify integration problems early and provide evidence of platform readiness. - Diagnostics and tooling that make complex robot systems easier to understand, debug and support. 🙌 You should apply if - You bring substantial experience integrating autonomous vehicles or similarly complex robotic systems, with deep practical understanding of how software, compute, sensors, networks and actuators interact. - You have led architecture and delivery for complex integration work, making sound technical decisions across software and hardware boundaries. - You have strong software-development skills in C++, Rust or comparable systems languages, and experience delivering production-quality software on Linux-based robotic, embedded or automotive platforms. - You can turn ambiguous requirements into clear designs, interfaces and implementation plans that other engineers can execute. - You have a track record of resolving difficult system-level problems through systematic investigation, on-target testing and a strong understanding of the underlying technology. - You understand ROS2 or similar middleware, distributed-system integration and the practical realities of vehicle bring-up. - You have raised the technical capability of a team through mentoring, design reviews and engineering standards. - You can influence technical decisions across teams and work with engineering management to connect architecture, delivery priorities and long-term investment. Experience delivering integrations across multiple vehicle or compute platforms, working with OEMs or hardware suppliers, and developing reusable integration frameworks would be particularly valuable. Experience with drive-by-wire, HiL testing, functional safety and fleet reliability would also be useful. 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and believe your experience would help us solve these challenges, we encourage you to apply even if you don’t meet every requirement. 🌱 Not ticking every box? That’s totally okay! If you’re passionate about autonomy and keen to learn, we encourage you to apply even if you don’t meet every requirement. More about Wayve: 🚀 Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natura
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