Tech talent as a service — embedded global engineering teams for product companies
Smart Working staffs engineering teams for 60+ clients across the UK and USA via remote-first hiring from Pakistan and India. The stack breadth (Python, Go, Rust, Java, Spring Boot, React, .NET, Kubernetes, AWS, GCP, Terraform) reflects a platform built to flex across multiple client architectures rather than a single vertical. Active hiring velocity — 59 roles posted in the last 30 days, all senior/mid-level engineering — signals aggressive scaling of their talent supply chain.
Smart Working is a talent-as-a-service firm that builds embedded, remote engineering teams for mid-market product companies. The model is full-lifecycle: vetting, onboarding, payroll, compliance, and performance management handled in-house. Clients span the UK and USA; engineers are hired locally in Pakistan and India and work extended overlap hours with client teams. The breadth of their tech specialties — from backend (Spring Boot, .NET Core, Node.js) through frontend (React, React Native) to DevOps (Docker, Kubernetes, Terraform, CI/CD) — allows them to staff diverse engineering demands. Beyond staffing, they provide architecture guidance and long-term partnership models rather than purely transactional placement.
Smart Working operates across Python, Go, Rust, JavaScript, Java, Spring Boot, React, .NET, C#, Node.js, TypeScript, Docker, Kubernetes, AWS, GCP, Azure, and Terraform. The breadth reflects their model: they hire into client stacks rather than impose a single technology choice.
London, United Kingdom. Operations span the UK and USA for client coverage, with engineering hiring and delivery from Pakistan and India.
Smart Working's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.