Modern warehouses must fulfil thousands of customer orders quickly while maintaining high levels of accuracy and operational efficiency. Traditional manual picking often requires associates to spend significant time walking between storage locations, making fulfilment slower, more labour-intensive, and increasingly difficult to scale as order volumes grow.

The Assisted Picking Platform was developed to improve warehouse fulfilment by combining autonomous mobile robots with intelligent software that guides warehouse associates through the picking process. Instead of workers travelling across the warehouse to collect items, robots transport inventory to the appropriate locations, reducing unnecessary movement and enabling associates to focus on picking and order completion.

As part of the product engineering leadership team, I contributed to the evolution of the Assisted Picking product from its early stages into a mature enterprise solution deployed across customer fulfilment centres. My responsibilities included product architecture, technical leadership, engineering execution, cross-functional collaboration, customer engagement, and mentoring engineering teams while continuing to contribute as a hands-on engineer.

The platform formed part of a broader warehouse automation ecosystem, helping customers improve operational efficiency, increase fulfilment throughput, and support the growing demands of modern omnichannel commerce.

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Technology Stack

• Java
• Spring Boot
• Apache Kafka
• PostgreSQL
• Redis
• Android
• Camunda
• Docker
• Kubernetes
• gRPC