Enterprise systems integrator with AI/ML and cloud modernization focus
Arohak is a mid-market IT services firm (201–500 employees) built around SAP, ServiceNow, and cloud engineering, now actively scaling AI/ML capabilities. The tech stack reveals a dual engineering orientation—enterprise integration (SQL Server, Oracle, Salesforce) alongside modern ML infrastructure (TensorFlow, PyTorch, scikit-learn)—while current hiring targets data and engineering roles at mid-to-senior levels, matching their project portfolio of ML model development, serverless AWS architecture, and application migration.
Arohak is a women-owned and diversity-certified IT services and consulting firm based in Monmouth Junction, New Jersey, founded in 2016. The firm serves mid-market and enterprise organizations across five service lines: Enterprise Applications (SAP and ServiceNow), Advanced Intelligence & AI Services, Enterprise Integration, Cloud & DevOps Engineering, and Application Development & Modernization. The company combines domain expertise in legacy system management (SQL Server, Oracle) with emerging capabilities in data engineering and generative AI, positioning itself for organizations navigating modernization and cloud migration.
Core: SQL Server, Oracle, SAP, ServiceNow, Salesforce. Cloud/DevOps: AWS (Lambda, DynamoDB, CloudFront), Azure, Terraform, Jenkins, GitLab CI/CD. Data/AI: Python, TensorFlow, PyTorch, scikit-learn, Pandas. Frontend: React, JavaScript, TypeScript, GraphQL.
ML model development and deployment, CI/CD pipeline implementation, scalable data pipeline development, cloud infrastructure design, serverless AWS integration, and application migration—reflecting focus on modernization and AI capabilities.
Arohak 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.