IT consulting and staff augmentation for AI, data and GIS engineering
Pro Integrate supplies specialist engineering talent through a consulting and staff augmentation model. Current job posts point to AI model training work: reinforcement learning environments, Gemini personalization evaluation and MCP tool-use reference solutions. Alongside that sits an Azure data stack (Data Factory, Synapse, Databricks, Fabric) and utility-grade GIS tooling (ArcGIS, ArcFM, SCADA). Hiring is accelerating, engineering-led and weighted toward junior and mid-level roles.
Pro Integrate is a privately held IT consulting and staff augmentation firm founded in 2017 and headquartered in New York. It employs 51–200 people and has operations in the United States, India, Malaysia, Indonesia and the Philippines. Its consulting work covers enterprise applications, cloud transformation, modernization and integration. Its staffing side places IT specialists with hard-to-find skills on enterprise client teams. Current placements span programming languages such as Python, Java, Go, Rust and C++, Azure data platforms, and geospatial systems.
Current job posts cover reinforcement learning environments for AI model testing, Gemini personalization feature evaluation, golden reference solutions for MCP tool use, and target technology architecture design.
Its stack includes Python, Java, Go, Rust, TypeScript and C++, plus Azure Data Factory, Synapse, Fabric, Databricks, Spark, SQL Server and PostgreSQL. It also uses GIS tools such as ArcGIS Pro, ArcFM and FME.
Pro Integrate is headquartered in New York, New York. It also has operations in India, Malaysia, Indonesia and the Philippines, and current hiring is focused on the United States.
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Pro Integrate'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.