Senior Software Engineer, Data

EngineersOfAI; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Wayve is seeking a Senior Software Engineer, Data to build and operate the Data Transfer Hub, a globally distributed system handling petabytes of sensor data daily. You’ll work with partners like Uber, Stellantis and Nissan to enable AI model training at scale.

You will design data pipelines, implement orchestration with Flyte and Kafka, and deploy on Azure, writing Terraform and Python to ensure reliability and observability across a cloud-first environment.

Qualifications

• Proven experience building and operating large-scale data transfer pipelines.
• Strong software engineering skills.
• Experience delivering & maintaining production systems.
• Experience with workflow orchestration (Flyte preferred).
• Experience building reliable, observable data systems.

Responsibilities

• Build and operate large-scale data transfer pipelines for video, LiDAR and sensor data from global partners at up to PB/day scale.
• Contribute to the technical design of the Data Transfer Hub with trade-offs on UX, reliability, throughput, cost, partner constraints, observability and operational support.
• Build parallelised, distributed data transfer pipelines using Flyte for workflow orchestration, Kafka/event-driven patterns for lifecycle tracing, and Azure for storage and transfer infrastructure.
• Help implement and evolve a globally distributed hub-and-spoke data transfer model to retrieve and share sensor data at scale with partners.
• Write infrastructure-as-code in Terraform and pipeline logic primarily in Python.
• Build reliable operational foundations, including retry strategies, backfills, data integrity checks, dashboards and alerting.
• Work on cloud-to-cloud and cross-cloud networking solutions, with Azure as the primary cloud platform.
• Once established, participate in an out-of-hours on-call and support rotation.
• Collaborate with product, commercial and partner-facing teams to understand constraints and deliver solutions that solve real customer and partner problems.
• Work in a fast-changing environment where requirements and partner deliverable dates evolve, while maintaining high engineering standards.

Skills

Large-scale pipelines

Software engineering

Production systems

Workflow orchestration

Observability

Tools

Flyte

Kafka

Azure

Terraform

Python

Job description

About us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.
In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The role

Portal is the cloud platform that connects Wayve to the outside world: handling data exchange with partners, surfacing AI insights, and enabling the commercial deployment of Wayve's AI driver on vehicles across the globe.

We're looking for a Senior Software Engineer, Data to help build Wayve's Data Transfer Hub: a mission-critical piece of infrastructure that will scale to transfer petabytes of sensor data per day from partners covering vehicles around the world.

This is a pivotal project at Wayve. You'll work as part of a small, high-autonomy team building a globally distributed hub-and-spoke data exchange system, working with partners like Uber, Stellantis and Nissan. Your work will help make Wayve's AI model training possible at scale.

Key responsibilities:

• Build and operate large-scale data transfer pipelines for video, LiDAR and sensor data from global partners at up to PB/day scale
• Contribute to the technical design of the Data Transfer Hub, making pragmatic trade-offs across UX, careliability, throughput, cost, partner constraints, observability and operational support
• Build parallelised, distributed data transfer pipelines using Flyte for workflow orchestration, Kafka/event-driven patterns for lifecycle tracing, and Azure for storage and transfer infrastructure
• Help implement and evolve a globally distributed hub-and-spoke data transfer model to retrieve and share sensor data at scale with partners
• Write infrastructure-as-code in Terraform and pipeline logic primarily in Python
• Build reliable operational foundations, including retry strategies, backfills, data integrity checks, lifecycle/state tracking, dashboards and alerting
• Work on cloud-to-cloud and cross-cloud networking solutions, with Azure as the primary cloud platform
• Once established, participate in an out-of-hours on-call and support rotation.
• Collaborate with product, commercial and partner-facing teams to understand constraints and deliver solutions that solve real customer and partner problems
• Work in a fast-changing environment where requirements and partner deliverable dates evolve, while maintaining high engineering standards

About you

In order to set you up for success as a Senior Software Engineer at Wayve, we’re looking for the following skills and experience.

Essential

• Proven experience building and operating large-scale data transfer, ingestion or data processing pipelines, ideally at multi-TB or PB scale
• Strong software engineering skills
• Experience delivering & maintaining production systems
• Experience with workflow orchestration for parallelised jobs; Flyte preferred, but Airflow, Prefect or similar tools are also relevant
• Experience building reliable, observable data s