Integration platform and nearshore engineering for enterprise software projects
Launchpad Technologies pairs its own iPaaS product with staffed integration and implementation engineers for client projects. Job posts cluster around AP automation and spend-management SaaS rollouts, pointing to a finance-operations implementation practice. The stack spans all three major clouds plus Terraform, Kubernetes and a heavy QA toolset (Selenium, Cypress, Playwright, TestRail), consistent with multi-client delivery. Senior engineering hiring is accelerating across the US and Argentina.
Launchpad Technologies is a privately held Vancouver, British Columbia company founded in 2018, with 51–200 employees. It offers an integration platform, Passport, for software integration and workflow automation. It also places IT specialists aligned to client time zones to deliver integration, data migration and enterprise architecture work. Its listed focus areas include Salesforce, MuleSoft, Apache Camel, ESB and API development. Current hiring spans the United States and Argentina, centered on engineering with smaller data, support and consulting needs.
Launchpad works across AWS, Azure and GCP with Terraform, Ansible, Docker and Kubernetes, builds in Java, C#, Python and Node.js, and tests with Selenium, Cypress, Playwright and Postman.
Launchpad is hiring in the United States and Argentina, mostly senior and mid-level engineering roles, with additional data and support openings. Hiring velocity is accelerating.
Job posts point to implementations of an AP automation platform and a spend-management SaaS platform, plus broader software implementation projects for clients.
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Launchpad Technologies Inc.'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.