Director, Integration Engineering

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

Penguin Solutions is seeking a Director, Integrations Engineering to lead a distributed engineering team responsible for validating technology integrations, operationalizing reference architectures, and delivering repeatable, production-ready AI Factory solutions.

This role sits at the intersection of Product Engineering and the field, combining technical leadership, customer engagement, and cross-functional execution to translate complex requirements into validated, scalable solutions.

Responsibilities

• Lead customer technical discovery, solution qualification, proofs of concept, integration planning, and deployment readiness for complex AI Factory environments.
• Drive end-to-end integration and interoperability validation across ClusterWareAI, GPU/HPC infrastructure, Kubernetes, networking, storage, and infrastructure management.
• Partner with Product, Software, Hardware, Services, Sales Engineering, and technology partners to validate reference architectures and resolve integration gaps.
• Transform customer-specific solutions and prototypes into repeatable architectures, automation, validation frameworks, runbooks, and implementation guidance.
• Translate customer and field insights into prioritized product and engineering improvements.
• Build and lead a high-performing, globally distributed engineering team, establishing clear priorities, ownership, capacity planning, and execution processes.
• Provide executive-level visibility into delivery commitments, risks, dependencies, and outcomes.
• Drive continuous improvement through automation, AI-assisted engineering, and strong technical documentation practices.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• 15+ years of experience in software, systems, infrastructure, platform, or integration engineering, including 5+ years in engineering leadership.
• Experience with AI/HPC infrastructure, GPU clusters, distributed systems, or data center infrastructure.
• Demonstrated experience leading customer-facing technical engagements and complex systems integration and validation.
• Strong ability to turn customer requirements into scalable, repeatable, and supportable solutions.
• Proven success leading distributed teams and influencing Product, Engineering, Services, and customer-facing organizations.
• Strong executive communication, prioritization, and organizational leadership skills.

Preferred Qualifications

• Experience with NVIDIA technologies, accelerated computing, and AI Factory architectures.
• Knowledge of Kubernetes, infrastructure automation, networking, storage, and cloud-native technologies.
• Experience with CI/CD, automated testing, infrastructure as code, and performance benchmarking.
• Experience applying AI and automation tools to engineering workflows.
• Experience supporting strategic partnerships and new product introductions

Location

Hybrid - Durham, North Carolina. The schedule is 3 days per week onsite.

Travel

20-25% domestic and international travel expected

Compensation & Benefits

The base pay range that the Company reasonably expects to pay for this position in North Carolina is $215,000 - $230,000; the pay ultimately offered may vary based on business considerations, including job-related knowledge, skills, experience, and education. The position is bonus-eligible, and there are medical, dental, and vision benefits available. There is a 401k saving plan and other benefits, such as Paid Time Off, Life Insurance, and an Employee Assistance Plan.

Inclusion & Belonging Statement

We are committed to creating an inclusive environment that embraces differences and fosters belonging for all.

Equal Opportunity Statement

We are an Affirmative Action/Equal Opportunity Employer and strongly committed to all policies which will afford equal opportunity employment to all qualified persons without regard to age, national origin, race, ethnicity, creed, gender, disability, veteran status, or any other characteristic protected by law.