Principal Software Engineer Manager (AI Infrastructure) - North America Software Center

TSMC•Washington, DC

9d•$166,800 - $241,800•Onsite

About The Position

TSMC Washington’s North America Software Center is seeking a Principal Software Engineer Manager to build and lead a high-performing team focused on the Enterprise AI Infrastructure Platform. This dual-impact leadership role combines technical expertise in distributed systems and AI platforms with people leadership. The manager will architect scalable, high-throughput AI infrastructure supporting internal and external foundation models, mentor engineering talent, and collaborate with teams across North America and Taiwan. The position is based on-site in Vancouver, Washington, during core business hours, Monday through Friday, 8 a.m. to 5 p.m. Additional hours may be required to meet project demands. The North America Software Center builds AI infrastructure, hybrid cloud platforms, data engineering ecosystems, and developer platforms used by thousands of engineers and high-volume manufacturing facilities worldwide. The role sets technical direction for AI platform capabilities and distributed infrastructure, supports engineering excellence and operational reliability, and partners with product managers, architects, and engineering leaders on long-term roadmaps. Applicants must be legally authorized to work in the United States; visa sponsorship or sponsorship takeover is not available. Employment is contingent on passing a background check and drug screening. Washington state regulations exclude cannabis use from the drug screening.

Requirements

Bachelor’s, master’s, or doctoral degree in Computer Science or a related field.
12 or more years of software engineering experience.
5 or more years leading architecture for distributed systems or cloud infrastructure.
3 or more years of hands-on experience designing enterprise AI platforms.
3 or more years of formal people management experience, managing teams of senior or staff engineers.
Strong technical communication skills for collaboration with global cross-functional teams.
Strong experience with LLM inference, Enterprise AI Gateway, AI serving infrastructure, GPU scheduling, multi-model AI architecture, and model lifecycle management.
Deep expertise with Kubernetes, Docker, Helm, ArgoCD, and service mesh.
Experience with AWS, Azure, or GCP.
Strong programming skills in one or more of Go, Python, or Java.
Experience with REST APIs, microservices, and SDKs.
Legal authorization to work in the United States; sponsorship is not available.
Ability to pass a background check and drug screening.

Nice To Haves

Experience with the NVIDIA GPU ecosystem, vLLM, TensorRT-LLM, Triton Inference Server, Ray, Kubeflow, or MLflow.

Responsibilities

Hire, lead, and develop a team of AI infrastructure and distributed systems engineers, fostering technical excellence, continuous learning, innovation, and psychological safety.
Set quarterly engineering roadmaps, establish agile delivery standards, and ensure high operational reliability.
Define long-term technical direction for the AI Platform, Enterprise AI Gateway, multi-model inference platform, GPU infrastructure, AI governance, and AI observability.
Design scalable platforms for LLM serving, GPU scheduling, model routing and lifecycle management, RAG infrastructure, vector databases, and AI orchestration.
Lead architecture for highly available AI services, multi-region deployment, disaster recovery, service mesh, distributed caching, event-driven architecture, and global load balancing.
Drive engineering best practices for Kubernetes, Platform-as-a-Service, and AI deployment automation.
Define technical strategy across multiple engineering teams and lead architecture reviews.
Mentor senior engineers and promote engineering excellence.
Influence technical decisions across North America and Taiwan.
Partner with product managers, architects, and engineering leaders to define long-term roadmaps.