At Penguin Solutions (Nasdaq: PENG) – The AI Factory Platform Company – we’re building a team of innovators who thrive on collaboration, creativity, and the opportunity to help shape the future of AI. As part of the AI technology revolution, our teams design, build, deploy, and manage AI factories for enterprises, sovereign AI initiatives, and neocloud providers worldwide.

Headquartered in Silicon Valley, California, Penguin Solutions operates globally through a network of R&D, manufacturing, and sales locations. For nearly three decades, we have operated at the intersection of memory and AI/HPC infrastructure. That engineering expertise positions us to power the next generation of AI workloads, from training to inference and agentic AI at scale.

Penguin Solutions brings together differentiated infrastructure software, advanced memory, compute systems, end-to-end services, and industry-leading partner solutions in a full-stack AI factory platform designed to help customers deploy and scale AI workloads with speed and precision.

At Penguin Solutions, we value ideas over hierarchy and believe in servant leadership, where leaders enable teams to do their best work. We empower employees to take ownership, drive innovation, and grow through challenging work, continuous learning, and exposure to advanced AI tools and technologies. With flexibility where it matters and a strong focus on outcomes, Penguin Solutions is a place to do your best work, grow your career, and make a meaningful impact.

Job Overview

The Integration Engineering team develops and validates the software solutions that power next-generation AI infrastructure. We work at the intersection of infrastructure, automation, AI platforms, and enterprise software to help customers deploy, operate, and scale AI environments with confidence.

As a Principal Systems Integration Engineer, you'll work across Penguin's AI Factory Platform and a broad ecosystem of technologies including Linux, Kubernetes, HPC, networking, storage, GPUs, AI frameworks, and cloud-native infrastructure to build, validate, and operationalize integrated solutions.

The team works collaboratively with Product Management, Software and Hardware Engineering, Solution Architects, and technology partners to evaluate new technologies, develop automation, solve complex integration challenges, and transform innovative ideas into production-ready capabilities.

Whether you're an experienced engineer or an early-career technologist with a strong systems background and a passion for learning, this role offers an opportunity to work on some of the most advanced AI infrastructure environments in the industry.

Responsibilities

Build and Validate AI Infrastructure Solutions

• Develop, integrate, and validate software solutions that enable enterprise AI infrastructure.
• Evaluate interoperability across Penguin software and partner technologies.
• Design and execute proof-of-concepts and technical evaluations.
• Help define best practices for deploying and operating AI infrastructure at scale.

Automate Everything

• Build automation using tools such as Ansible, Python, GitLab CI/CD, Helm, and Kubernetes.
• Improve deployment, validation, and operational workflows.
• Create reusable tooling that increases reliability and repeatability.

Solve Complex Systems Problems

• Troubleshoot issues that span software, infrastructure, networking, storage, Kubernetes, and AI platforms.
• Work alongside engineering teams to identify root causes and drive technical solutions.
• Contribute to the continuous improvement of Penguin's AI Factory Platform.

Learn, Experiment, and Innovate

• Explore emerging technologies across the AI infrastructure ecosystem.
• Evaluate new open-source and commercial technologies.
• Contribute ideas that influence future products and solution architectures.
• Continuously expand your technical expertise across infrastructure and AI technologies.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 8+ years of experience managing and scaling Linux-based production environments.
• Deep expertise with Kubernetes architecture, deployment, and operations.
• Strong experience with infrastructure automation and Infrastructure as Code (Ansible preferred).
• Advanced scripting skills in Python, Bash, or similar languages.
• Expertise with Git, CI/CD pipelines, and modern cloud-native development practices.
• Proven use of AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude Code, ChatGPT) to drive productivity and engineering efficiency.
• Strong problem-solving and troubleshooting skills in complex distributed environments.
• Excellent communication, collaboration, and technical leadership skills.
• Experience leading cross-functional initiatives, mentoring engineers, and influencing technical strategy.

Preferred Qualifications

• Experience with one or more of the following:
  • DevOps or Platform Engineering
  • AI or machine learning infrastructure
  • GPU computing
  • Slurm or HPC environments
  • Enterprise storage
  • Networking
  • Containers and cloud-native technologies
  • Observability platforms
  • CI/CD pipelines

Location

Hybrid – Bangalore, India