VAST Data is looking for a Technical Release Manager to join our growing team!
This is a great opportunity to be part of the fast-growing infrastructure company in history. In just a few short years, we’ve shaken up the industry by challenging traditional architecture models and introduced a revolutionary set of storage possibilities through our Universal Storage platform.
Now we are taking on the next challenge of building the Vast Data Platform for the AI era.
Our success has been built through incredible leadership and motivated employees who want to leverage their skills & experiences to make a real impact.
This is your opportunity to lead the end-to-end release development process. Starting from release content definition, through architecture and design, to implementation, testing and field delivery. Apply your technical and analytical skills to directly impact the product and the process.
You will work with the R&D leaders, architects, tech leads and best-of-class development teams to deliver breakthrough technology in a fast-paced release cycle.
Come join the disruption, make your mark, and be a part of the amazing team introducing the new era of data storage!
Bachelor's or Master’s degree or equivalent experience in Computer Science/Engineering
Proven experience as SW engineer and a Release manager or SW project leadership with 5+ years of overall experience.
Great interpersonal skills.
Excellent problem-solving, analytical thinking and critical thinking abilities.
Ability to self-manage, self-start, lead technically and communicate effectively.
Strong experience in C/C++ software engineering design, coding, integration, and debugging
Understanding of Linux operating system
Solid networking knowledge (OSI network layers, TCP/IP) — advantage
Knowledge block-level Storage / file systems — advantage
Python scripting — advantage

The Operating System for the Thinking Machine.
VAST delivers the first AI Operating System, natively unifying and orchestrating storage, database, and compute to unleash the true power of agentic computing and data-intensive applications.