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 Sr. 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.
5+ years of experience administering and supporting Linux-based production environments.
Hands-on experience deploying and managing Kubernetes in production environments.
Experience with infrastructure automation and configuration management (Ansible preferred).
Proficiency in scripting and automation using Python, Bash, or similar languages.
Experience with Git, CI/CD pipelines, and modern software development practices.
Experience leveraging AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude Code, ChatGPT) to improve engineering productivity.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent written and verbal communication skills, with the ability to collaborate across cross-functional teams.
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
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