Staff augmentation and managed services for data, cloud, and enterprise engineering
Infinite Tek (formerly TribolaTech) operates a managed staffing and engineering services business focused on data platforms, cloud migration, and enterprise DevOps. The tech stack is heavily AWS-anchored (Lambda, SQS, RDS, CodePipeline) with Kafka for event streaming and Kubernetes for orchestration — a pattern that mirrors the infrastructure modernization work they deliver to clients. Current hiring is skewed toward senior engineering and a Product Director role, suggesting internal scaling of delivery capability and product maturity rather than typical staff-augmentation-only growth.
Notable leadership hires: Product Director
Infinite Tek delivers integrated engineering teams and managed services to financial services, healthcare, and enterprise SaaS companies. The service portfolio spans data platforms and AI engineering, cloud-native architecture, DevOps transformation, and end-to-end product development, with an emphasis on delivery governance and accountability beyond pure staff augmentation. Headquartered in San Ramon, California, the company operates a global delivery model and serves mid-market to enterprise clients navigating cloud migration, Kubernetes adoption, and integration complexity across legacy and modern systems.
AWS (Lambda, SQS, RDS, CodePipeline, VPC, IAM, CloudWatch), Kafka, Kubernetes, Docker, PostgreSQL, Oracle, MySQL, DynamoDB, TypeScript, Python, Node.js, Jenkins, Bamboo, Jira, and Confluence.
Workday implementation and integration, AWS cloud migration programs, infrastructure-as-code initiatives, and Kubernetes and DevOps transformation programs.
Infinite Tek 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.