At IBM Infrastructure & Technology we design and operate the systems that keep the world running. From high-resiliency mainframes and hybrid cloud platforms to networking automation and site reliability. Our teams ensure the performance security and scalability that clients and industries depend on every day. Working in Infrastructure & Technology means tackling complex challenges with curiosity and collaboration. You’ll work with diverse technologies and colleagues worldwide to deliver resilient future-ready solutions that power innovation. With continuous learning career growth and a supportive culture IBM provides the opportunities to build expertise and shape the infrastructure that drives progress.
The IBM Z organization is looking for an AI on Z Software Manager to work with Machine Learning topics - primarily zOS and technical enablement for business scale out of AI. An ideal candidate would be experienced with AI concepts familiar with Linux on Z and zOS and comfortable in technology discussions. This candidate should be comfortable learning & teaching new skills a good people manager and leader. The candidate should be a good listener and be able to find solutions outside the box for problems to increase productivity of the team and streamline processes. Being a self starter with ability to work on new missions and deal with uncertainty would be a plus.
The AI on Z team is responsible for solutioning of enterprise customer's business problems by creating custom solutions demoable assets proof of concepts etc. to showcase the AI capabilities of the platform and especially the onboard AI accelerator. Additionally the team is also contributing in a big way towards the development of AI Toolkit that has the necessary packages as well as platform specific optiizations & enhancements that provide competitive differentiation. The team is tasked with enabling ML/DL inferencing solutions on the IBM Z Mainframe systems. We closely collaborate with the research labs and other development teams of IBM as well as interface with the global maintainers of Open Source communities.
As an Engineering Manager you will primarily be responsible in leading/managing the AI on Z team focussed on enabling the development and client adoption of the AI stack on zOS and LoZ Systems on IBM Z Server systems architecture.
In the capacity of management leader you will be working with peers and stakeholders to ensure IBM business continuity. You will be responsible for the development team with a joint and end-to-end ownership of the product development managing delivery schedules and assure highest quality release with maximum exploiter/customer satisfaction.
Essentially :
• Hire and managing highly talented engineers skilled in Linux base OS and associated Hybrid Cloud and AI sub-systems
• Focus on Employee engagement Growth Skill building Innovation and well-being towards retaining highly talented engineers
• Enable collaboration with distro partners to upstream the modules to open source community.
• Take End to End responsibility of product delivery and release by applying Design Thinking & Agile practices in product design development & test. Make sure that commitments are met in a cross functional matrix which unblock customer engagements and enable key AI features on the IBM Z Mainframes.
• Motivate the team in applying processes and best practices in delivering great user experience and quality products for IBM’s Server Systems
• Ensure Business Compliance and Integrity is maintained across the team
• Collaborate with peers and stakeholders to share/apply best practices at increasing efficiency in the process/product methodologies
1. Demonstrated leadership with around 15 plus years of experience in the systems industry. Should have 5 plus years of experience exclusively in leading teams of 15-30 people. Proven ability to lead teams and take ownership of end-to-end activities.
2. Ability to understand AI solutions and lead complex AI missions.
3. Strong working experience in the big-endian systems network concepts GPUs.
4. Strong grounding in traditional AI methodologies covering machine learning and deep learning frameworks with the capacity to guide and mentor team members.
5. Mastery of Python C++ and relevant ML libraries (e.g. TensorFlow PyTorch) for developing top-tier production-grade products. Proven ability to lead technical teams in the implementation of complex solutions.
6. Familiarity with zOS platforms and experience in zOS app and system development demonstrating leadership in guiding teams through the development lifecycle. Familiarity with Linux systems would be an added advantage.
7. Experience in Generative AI is highly advantageous with the ability to provide leadership and direction in exploring innovative AI techniques.
8. Familiarity with processes for secure development life cycle of Products.