Engineering Manager, AI Data Platforms & Quality

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Manufacturing Systems and Infrastructure (MSI) team is an engineering

organization under the Product Operations org. MSI is responsible for the

design, development, and maintenance of systems tools, services, and

applications required to efficiently run manufacturing operations at scale

across global factory sites. The ideal candidate is a strong engineering leader

with deep expertise in data platforms, AI data engineering, and modern AI

application architectures. This leader will build and scale the foundational

capabilities for AI data lifecycle management—including data ingestion,

curation, validation, quality, governance, metadata management, and

observability—while delivering scalable AI-powered data products and platforms.

Success in this role requires close partnership with AI/ML, product, and

business teams to accelerate the development of high-quality data assets that

fuel enterprise AI innovation.

DESCRIPTION

As the Engineering Manager, AI Data Platforms & Quality within the MSI

organization, you will lead the team's expanded charter to build next-generation

AI data products, data platforms, and data quality capabilities that enable

GenAI, agentic AI, and embodied AI initiatives. You will define and drive the

technical strategy for transforming enterprise, operational, and multimodal data

into trusted, AI-ready assets that power intelligent applications, AI agents,

analytics, and automated workflows.

MINIMUM QUALIFICATIONS

Experience leading solution and data engineering teams building large-scale,

production-grade systems. Strong background in data engineering, distributed

systems, and cloud-based data platforms. Proven experience designing and

building scalable data products, data pipelines, APIs, and platform services.

Experience with AI data lifecycle management, including dataset curation,

validation, quality evaluation, metadata management, lineage, and governance.

Strong expertise in AI Data Platforms & Engineering, including Python, SQL,

Spark, Airflow, Kafka, data pipelines, distributed systems, and modern data

lake/lakehouse architectures. Experience building AI Data Curation & Quality

capabilities, including dataset engineering, validation frameworks, data

profiling, observability, and data quality metrics. Understanding of GenAI

enablement technologies, including LLM applications, RAG architectures,

embeddings, and AI agent workflows. Experience with cloud and infrastructure

technologies, including AWS/GCP/Azure, Kubernetes, Docker, CI/CD, and scalable

production systems. Demonstrated ability to define technical strategy, drive

architecture decisions, lead complex execution, and collaborate effectively

across cross-functional teams.

PREFERRED QUALIFICATIONS

Experience building AI data platforms or infrastructure supporting LLM

applications and AI products. Experience with multimodal data including text,

image, video, sensor, or operational datasets. Experience building data quality

frameworks, AI evaluation pipelines, or dataset management platforms. Experience

translating emerging AI technologies into scalable enterprise solutions. Strong

communication skills with the ability to influence technical direction across

organizations.