Director, Integration Engineering

Penguin Solutions•Durham, NC

1d•Hybrid

About The Position

Penguin Solutions is seeking a Director, Integration Engineering to lead a distributed engineering team responsible for validating technology integrations, operationalizing reference architectures, and delivering repeatable, production-ready AI Factory solutions. The role sits between Product Engineering and the field, combining technical leadership, customer engagement, and cross-functional execution to turn complex requirements into validated, scalable solutions. The Director will lead customer technical discovery and integration activities, validate interoperability across AI Factory technologies, and work with internal teams and technology partners to resolve integration gaps. The role also converts customer-specific solutions and prototypes into repeatable architectures, automation, validation frameworks, runbooks, and implementation guidance, while feeding customer and field insights into product and engineering priorities. The position builds and leads a high-performing, globally distributed engineering team and provides executive-level visibility into delivery commitments, risks, dependencies, and outcomes. It is hybrid in Durham, North Carolina, with three days per week onsite and an expected 20–25% of domestic and international travel.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a 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.

Nice To Haves

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.

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.