Manager, Data and AI Engineering

NVIDIA•Santa Clara, CA

1d•$200,000 - $322,000

About The Position

The Manager, Data and AI Engineering will lead the development of a next-generation autonomous data intelligence platform for Supply Chain Operations. The role combines technical architecture and hands-on engineering with delivery leadership and people management, identifying high-impact opportunities and building production solutions that provide measurable business value. The manager will partner with business and technical collaborators to translate operational challenges into secure, scalable data and AI solutions, while overseeing delivery across multiple concurrent initiatives. The position includes designing cloud-native data and AI platforms and pipelines; enabling AI applications and advanced analytics; establishing data quality, observability, and production reliability practices; and providing technical leadership across the full project lifecycle, from discovery and planning through rollout. The manager will mentor engineers, build team capability, and foster accountability, innovation, and continuous improvement.

Requirements

Master's or bachelor's degree in Computer Science or Information Systems, or equivalent experience.
10+ years of overall experience in Data Engineering, Software Engineering, or web application development.
At least 4+ years in a leadership or engineering management role.
Willingness to remain hands-on by coding, prototyping, and building production systems.
Intimate knowledge of the AWS ecosystem, including Amazon S3, EC2, IAM, Lambda, and API Gateway.
Proven experience operationalizing LLMs into autonomous agents that can plan, use tools, and implement multi-step workflows.
Deep expertise in Apache Spark, PySpark, Delta Lake, and Databricks Workflows.

Nice To Haves

Hands-on experience scaling Unity Catalog.
Active Databricks certifications, such as Data Engineer Professional or Generative AI Engineer Associate.
Active AWS certifications, such as Certified Data Engineer – Associate or Solutions Architect – Professional.
Experience managing multi-functional teams combining data engineers with front-end and back-end software developers.
Knowledge of supply chain business processes for Plan, Make, Deliver & Services.

Responsibilities

Design and build scalable data and AI platforms using Databricks, AWS, and modern cloud-native engineering patterns.
Deliver ETL/ELT, streaming, and CDC pipelines using technologies such as Spark, Kafka, Delta Lake, and AWS-native services.
Enable AI-powered use cases, including RAG applications, AI agents, tool-calling workflows, and data-driven web applications.
Design data models using Star Schema, Snowflake Schema, and Data Vault patterns, considering query performance, governance, and extensibility.
Implement data quality frameworks, observability, alerting, and monitoring to support pipeline integrity and production reliability.
Build data foundations for GenAI, agentic AI, and advanced analytics, including RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration patterns.
Partner with product, business, analytics, and AI collaborators to turn requirements into secure, scalable, production-ready solutions.
Oversee resource planning, prioritization, project execution, and delivery across multiple concurrent initiatives.
Mentor engineers, develop technical capability across the team, and foster accountability, innovation, and continuous improvement.
Provide hands-on technical leadership in architecture, design reviews, implementation guidance, and production readiness.
Manage the full lifecycle of data engineering projects, from discovery and planning through execution and production rollout.
Write code, prototype, and build production systems alongside the team.