Senior Software Engineer, Data

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 Portal Team

Portal is the cloud platform that connects Wayve to the outside world: enabling data exchange with partners, surfacing AI insights and supporting the commercial deployment of our AI Driver in vehicles around the globe.

As a Senior Software Engineer, Data, you’ll join a small, high-autonomy team building Wayve’s Data Transfer Hub—mission-critical infrastructure designed to transfer petabytes of sensor data per day from global partners. Working with partners such as Uber, Stellantis and Nissan, you’ll help build the data foundations that make AI model training possible at scale.

🧠 Your day-to-day

• Build and operate large-scale pipelines that transfer video, LiDAR and other sensor data from global partners.

• Shape the technical design of the Data Transfer Hub, making pragmatic trade-offs across user experience, reliability, throughput, cost, partner constraints, observability and operational support.

• Write pipeline logic primarily in Python and manage infrastructure as code with Terraform.

• Work closely with product, commercial and partner-facing teams to understand constraints and solve real customer and partner problems.

• Take ownership of production systems, maintaining high engineering standards as requirements and partner delivery timelines evolve.

• Once the service is established, participate in an out-of-hours on-call and support rotation.
  

🧩 What you’ll be working on:

• A globally distributed Data Transfer Hub: implement and evolve a hub-and-spoke model for retrieving and sharing sensor data with partners at up to petabyte-per-day scale.

• Parallelised, distributed transfer pipelines: use Flyte for workflow orchestration, Kafka and event-driven patterns for lifecycle tracing, and Azure for storage and transfer infrastructure.

• Reliable, observable operations: build retry strategies, backfills, data integrity checks, lifecycle and state tracking, dashboards and alerting.

• Cloud-to-cloud and cross-cloud connectivity: develop networking and large-scale file-transfer solutions, with Azure as the primary cloud platform.

• Performance and efficiency at scale: improve throughput, reliability and cost efficiency while accommodating different partner environments and constraints.
  

🙌 You should apply if:

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