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Calfus in Pleasanton, CA is seeking an early-career Software Engineer focused on DevOps and platform work. You will automate builds, containerize services, and maintain healthy pipelines across customer engagements.
The role requires Linux expertise, Python and shell scripting, Docker, and backend skills (Node.js, Java, Python, or Go). You'll work onsite in Pleasanton and collaborate across teams to improve deployment and developer experience while upholding security practices.
At Calfus, we are known for delivering cutting-edge AI agents and products that transform businesses in previously unimaginable ways. We empower companies to harness the full potential of AI, unlocking opportunities they never imagined possible before the AI era. Our software engineering teams are highly valued by customers, whether start-ups or established enterprises, because we consistently deliver solutions that drive revenue growth. Our ERP solution teams have successfully implemented cloud solutions and developed tools that seamlessly integrate with ERP systems, reducing manual work so teams can focus on high-impact tasks.
None of this would be possible without talent like you! Our global teams thrive on collaboration, and we’re actively looking for skilled professionals to strengthen our in-house expertise and help us deliver exceptional AI, software engineering, and solutions using enterprise applications.
As one of the fastest-growing companies in our industry, we take pride in fostering a culture of innovation where new ideas are always welcomed without hesitation. We are driven and expect the same dedication from our team members. Our speed, agility, and dedication set us apart, and we perform best when surrounded by high-energy, driven individuals.
To continue our rapid growth and deliver an even greater impact, we invite you to apply for our open positions and become part of our journey!
We are looking for an early-career Software Engineer who leans heavily toward DevOps and platform work. You will spend your days in Linux, writing Python and shell to automate the parts of our delivery process that should not be manual, packaging services into containers, and keeping build and deployment pipelines healthy for engineering teams across multiple customer engagements.