IT staffing, managed teams and nearshore/offshore engineering services
The Methodical Group places and manages technical talent across the US, Brazil and the Philippines, and its current job posts read like client delivery work: a mainframe-to-data-lake migration, healthcare eligibility modernization and RTLS deployments. The stack is Microsoft-centric (C#, .NET, Blazor, Azure DevOps), with OpenAI, Gemini, Cursor and Codex pointing to AI-assisted development. Hiring is accelerating and skews to senior engineers.
The Methodical Group is a privately held staffing and IT services firm founded in 1998 and headquartered in St Petersburg, Florida. It provides IT staffing, technical recruiting, contract and permanent placement, managed services, managed teams and business process outsourcing. Delivery runs through onshore, nearshore and offshore models, with hiring in the United States, Brazil and the Philippines. The company employs 201–500 people. Its engineering work spans .NET and Azure application development, data platform modernization, test automation and real-time location system support.
Its stack centers on Microsoft: C#, .NET, ASP.NET, Blazor, .NET MAUI, SQL Server and Azure services. It also uses Java, Python, TypeScript, PostgreSQL, MQTT, Selenium, Playwright, and AI tools such as OpenAI, Gemini and Cursor.
The Methodical Group is hiring in the United States, Brazil and the Philippines. This matches its onshore, nearshore and offshore staffing model.
Current projects include a legacy mainframe-to-data-lake transition, a curated dataset platform and enterprise healthcare eligibility modernization. Other work covers RTLS hardware installation and test automation framework upgrades.
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The Methodical Group'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.