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Strong employer brand and metro location but senior, specialized AI+time-series requirements narrow candidate pool.
Requires deep vehicle telemetry, time-series modeling and agentic AI expertise, limiting cross-industry transferability.
Multiple mandatory requirements: 10+ years, Staff-level IC, GCP streaming, time-series modeling, and agentic AI expertise.
Lead the design and implementation of a modern, scalable streaming data architecture for connected vehicle data at global scale, focusing on AI-driven automation and insight generation.
Provide technical leadership and mentorship to Staff and Senior Staff Engineers (~80+ engineers), driving alignment through architecture reviews and standards.
Own technology strategy for cost-efficient, resilient cloud data infrastructure integrating AI and agentic flows to enable proactive business decisions for 2026+ model vehicles.
Bachelor's degree in Computer Science, Data Engineering, or related field; Master’s or PhD preferred.
10+ years professional experience with software and data engineering, including architecting large-scale (petabyte-scale) streaming and distributed systems.
Proven technical leadership experience as Staff or Senior Staff Engineer leading large engineering organizations (50-100+ engineers).
Expertise in database and specialized time-series data modeling, applied AI with agentic workflows, and Google Cloud Platform stack (BigQuery, Dataflow, Vertex AI); mastery of Kafka or Pub/Sub.
Highly experienced IC leader comfortable bridging software, data engineering, and AI with hands-on coding and high-level architectural decision-making.
Strategic thinker focused on modernizing legacy systems towards AI-driven, autonomous data ecosystems with an emphasis on operational efficiency and cost optimization.
Demonstrated success leading large, complex projects at scale involving petabyte-level IoT datasets and introducing innovative AI/ML solutions for real-time data insights.