Principal Engineer, Agentic AI Data and Insights

• Redefine data analysis architecture. Design a shared component ecosystem (skills, sub-agents, RAG systems, embeddable UIs) across harnesses (Plx, Cloud, Jetski).
• Guide Core, Cloud, and GDM teams. Resolve complex disputes and ensure enterprise-wide coherence, bridging internal systems with external cloud standards.
• Act as Insights' unifying technical liaison, collaborating with VPs and senior ICs to establish common infrastructure.
• Bridge technical gaps, specifically translating cloud-generated ANSI SQL into the specialized Google SQL required internally.
• Align senior ICs and disparate in-flight efforts to work on the highest-impact data analysis problems. Mentor staff/senior staff engineers. Lead the cultural transition from traditional software engineering to AI-orchestrated development models.

Minimum qualifications:

• Bachelor's degree in Computer Science or a related technical field or equivalent practical experience.
• 15 years of experience in software engineering.
• Experience designing, building, and maintaining large-scale distributed systems.
• Experience serving as a senior technical leader (e.g., principal engineer, senior staff engineer, or equivalent) overseeing portfolios and multiple engineering teams.
• Experience in architectural design and systems integration for multi-stakeholder, enterprise-grade platforms.

Preferred qualifications:

• Master’s degree or PhD in Computer Science, Machine Learning, Computer Engineering, or a related highly technical field.
• Experience with modern data technologies, distributed computing frameworks, or open-source data lakehouse standards (e.g., Iceberg, Spark, or equivalent).
• Experience building high-quality, compelling developer tools or standardized component ecosystems that teams voluntarily adopt.
• Knowledge of agentic harnesses, large language models, agentic AI workflows (such as sub-agent configuration, skills, and RAG systems), and developer ecosystems.
• Extensive technical domain expertise in large-scale data analysis, database systems, or Business Intelligence (BI).
• Proven track record of working with large-scale, unstructured, and "messy" data ecosystems at scale.

• Bachelor's degree in Computer Science or a related technical field or equivalent practical experience.
• 15 years of experience in software engineering.
• Experience designing, building, and maintaining large-scale distributed systems.
• Experience serving as a senior technical leader (e.g., principal engineer, senior staff engineer, or equivalent) overseeing portfolios and multiple engineering teams.
• Experience in architectural design and systems integration for multi-stakeholder, enterprise-grade platforms.