IT services and staffing for Fortune 500 enterprises modernizing legacy systems
Infobahn is a 1,001–5,000-person services firm focused on legacy modernization and enterprise integration for Fortune 500 clients. The tech stack reveals a heavy tilt toward integration middleware (MuleSoft, Kafka, Oracle, SQL Server) and thermal/CAD tooling (Teamcenter, NX, SolidWorks, Creo), with active projects spanning Mule 3-to-4 migration, CloudHub 1.0-to-2.0 upgrades, and microservices architecture rewrites. Hiring is accelerating across engineering and leadership roles, signaling concurrent delivery pressure and internal skill gaps in modernization-adjacent areas like asynchronous messaging and order-management systems.
Founded in 1996 and headquartered in San Jose, Infobahn delivers full-lifecycle IT consulting and custom application development to Fortune 500, mid-market, and startup companies. Services span enterprise and consumer application development, cloud and web implementation (Salesforce, SAS), data migration, mobile solutions, test automation, and staffing across onsite, offsite, and offshore delivery models. The company operates across North America and India, with current project focus on thermal validation, enterprise integration modernization, and omnichannel order-management platforms.
Primary stack: Oracle Database, SQL Server, Java, C++, MuleSoft, Kafka, Salesforce, Snowflake, Jira, and CAD tools (Teamcenter, NX, SolidWorks, Creo). Currently adopting Mule and managing migration from Mule 3 to Mule 4 and CloudHub 1.0 to 2.0.
Yes. Infobahn has 11 active roles with accelerating hiring velocity, including 6 senior and 3 mid-level engineering positions. Openings are in the United States and India.
Current projects include modernizing legacy systems into microservices, implementing asynchronous messaging (Anypoint MQ and Kafka), thermal validation for client products, and IBM Sterling order-management system implementations with omnichannel optimization.
Infobahn Softworld 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.