Nearshore software development and staff augmentation from Mexico
Towa Software is a nearshore development shop serving US companies with augmented engineering teams and dedicated squads from Mexico. The tech stack—GCP, Vertex AI, BigQuery, Python, React, Node.js, .NET, and emerging LLM tooling (LangChain, CrewAI, RAG)—reflects both legacy modernization work and active AI integration. Current hiring is engineering-heavy with mid- to principal-level roles, and projects cluster around CI/CD, QA automation, and migrating off Angular; this hiring velocity and project mix signal investment in operational efficiency and AI-driven tooling rather than new product expansion.
Towa Software, founded in 2002, operates a nearshore staffing model pairing US companies with Mexican engineering teams under what the company calls an 'Engineering Warriors' methodology. The company provides three engagement models: staff augmentation, dedicated teams, and co-managed squads. Specializations span full-stack development (React, Node.js, .NET), data engineering (BigQuery, Dataflow, Power BI), cloud infrastructure (GCP, Kubernetes), and emerging AI (Vertex AI, LLM integrations). The company employs 201–500 people and is based in San Antonio, Texas.
Primary stack: GCP, Python, React, Node.js, .NET, C#, MongoDB, BigQuery, Vertex AI. Emerging: LangChain, LangGraph, CrewAI, RAG. Also: Kubernetes, SQL Server, Power BI, Angular, TypeScript, WordPress.
AI-driven QA automation, CI/CD pipeline improvements, legacy system modernization (especially Angular migration), API integrations, and frontend upgrades. Also addressing data environment optimization and high-availability infrastructure.
Towa Software'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.