Real-time retail AI platform for autonomous stores and inventory tracking
Sensei operates a real-time retail intelligence platform built on AWS, Kubernetes, Kafka, and Protocol Buffers—a stack optimized for high-frequency data ingestion and low-latency inference at scale. The company is actively hiring engineering-heavy (9 roles), with emerging sales infrastructure (VP of Sales, 3 open roles), reflecting a transition from product-focused to sales-led growth. Platform stability and on-prem/cloud hybrid scalability surface repeatedly in pain points, indicating the core engineering challenge is operationalizing a distributed system across retail sites.
Notable leadership hires: VP of Sales
Sensei builds a real-time AI platform that monitors store activity, product interactions, and shopper behavior for retailers. The product powers autonomous points of sale and traditional retail locations, enabling live inventory tracking and operational insights. Founded in 2017 and based in Castelo Branco, Portugal, the company operates across Portugal, Spain, Italy, France, and Brazil. Active projects span autonomous store infrastructure, cloud IaC implementation, sales process standardization, and regional go-to-market expansion—signaling both product maturation and geographic scaling. The organization employs 51–200 people, hiring exclusively in Portugal.
AWS, Kubernetes, Docker, Kafka, gRPC, Protocol Buffers, Python, Terraform, Datadog, Prometheus, and Grafana. The stack reflects distributed systems and real-time data streaming infrastructure.
Portugal only. All current hiring is localized to the country of headquarters (Castelo Branco).
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