Application Engineer Lead, Supplier Quality Platforms

Google•Kirkland, WA

17d•$163,000 - $236,000

About The Position

Lead end-to-end technical architecture and full-stack software development for a predictive supplier quality and risk intelligence platform. The role covers requirements gathering, web development, software development, testing, documentation, training, implementation, ongoing support, and maintenance for in-house and customer-facing applications. The engineer works with cross-functional teams using UI and functional specifications or prototypes, and takes ownership to innovate in response to user and customer needs. The role connects hardware manufacturing telemetry across critical data center programs with scalable enterprise cloud services. It builds an AI-ready data ecosystem for proactive visibility into global supply-chain risks, provides technical direction to a pod of application and data engineers, and partners with Global Supply Chain Managers and other stakeholders. The position is expected to involve coding 50–70% of the time. The AI and Infrastructure team develops capabilities and insights at scale for Google customers, including Googlers, Google Cloud customers, and Google users worldwide.

Requirements

Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience.
8 years of experience working with general-purpose programming languages such as Python, Java, Go, or C++.
8 years of experience in enterprise application development and data engineering, including designing data pipelines, databases, and web services such as REST or SOAP APIs.
5 years of experience leading system architecture, integrating third-party systems, and mentoring engineering teams.

Nice To Haves

Master's degree in Computer Science, MIS, or a related technical field, or equivalent practical experience.
Domain expertise in supply-chain operations, hardware manufacturing data such as FPY and cycle time, or MES.
Experience developing AI/ML-enabled applications or integrating cloud-native AI services, and designing data architectures optimized for ML workloads.
Experience with full-stack development, modern web frameworks, and cloud-native data-processing pipelines.
Experience designing secure external data-sharing portals, enterprise Identity and Access Management integration using OAuth2/OIDC, and data governance.
Exceptional cross-functional communication skills and demonstrated ability to work face-to-face with internal business stakeholders to translate complex requirements into technical solutions.

Responsibilities

Architect, build, and deploy scalable enterprise applications and secure external-facing partner portals.
Design and implement web services and synchronous microservices, such as REST APIs and FastAPI, to integrate external contract manufacturing systems with internal data warehouses.
Architect an AI-ready data foundation and semantic serving layer for supplier manufacturing telemetry, including automated pre-flight quality validation and feature pipelines optimized for predictive machine-learning models and downstream AI agents.
Provide technical direction for a cross-functional pod of extended-workforce engineers; establish code-quality standards, lead system-design reviews, and manage end-to-end application architecture.
Partner with Hardware Quality Engineers and Supply Chain Managers to translate physical manufacturing metrics into dimensional data models and automated pipelines.
Lead requirements gathering, software development, testing, documentation, training, implementation, ongoing support, and maintenance for in-house and customer-facing web applications.