Principal Engineer – Public Cloud Data

• Define the target-state architecture for cloud-native data, analytics, AI/ML, and Agentic AI platforms
• Establish engineering standards, reference architectures, reusable patterns, and technical governance across the enterprise
• Drive modernization of legacy data platforms into scalable cloud-native ecosystems
• Lead technology evaluations and strategic adoption of emerging public cloud capabilities
• Architect and scale enterprise lakehouse, data mesh, streaming, and real-time analytics platforms
• Define standards for data ingestion, transformation, governance, metadata management, lineage, and data quality
• Enable self-service data products and analytics capabilities across business lines
• Lead development of Agentic AI solutions that automate engineering, operations, governance, and analytics workflows
• Define enterprise frameworks for AI agents, orchestration, reasoning engines, MCP-based integrations, and human-in-the-loop controls
• Architect AI-enabled automation for data onboarding, pipeline generation, metadata enrichment, policy enforcement, data quality validation, incident remediation, and operational intelligence
• Establish standards for responsible AI, explainability, model governance, and auditability
• Provide technical leadership across public cloud compute, storage, networking, security, AI, analytics, and Dev Ops ecosystems
• Drive platform reliability, scalability, resiliency, observability, disaster recovery, and operational excellence
• Partner with engineering teams to implement Infrastructure as Code, platform automation, and self-service capabilities
• Establish SLOs, reliability metrics, and engineering KPIs
• Partner with Cyber Security, IAM, Risk, Audit, and Regulatory Compliance teams
• Ensure cloud platforms meet enterprise security, governance, privacy, and regulatory standards
• Architect secure-by-design and compliance-by-design platform capabilities
• Drive implementation of AI governance controls for enterprise-scale Agentic AI adoption

• 7+ years of Engineering experience, or equivalent demonstrated through work experience, training, military experience, education
• 7+ years designing enterprise-scale data and analytics platforms
• 5+ years delivering AI/ML, Generative AI, or Agentic AI solutions in complex enterprise environments
• Proven experience leading enterprise-wide cloud transformation initiatives
• Deep expertise in one or more public cloud platforms;
  Google Cloud Platform preferred
• Experience with Microsoft Azure and/or Amazon Web Services
• Strong experience with data lakehouse architectures
• Experience with Big Query, Snowflake, Databricks, Starburst, or equivalent platforms
• Experience with streaming and event-driven architectures
• Experience with data governance, metadata, lineage, and catalog solutions
• Experience with Kubernetes and container platforms
• Experience with Infrastructure as Code and Dev Ops automation
• Experience designing enterprise AI platforms and MLOps frameworks
• Experience with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Agentic AI architectures, multi-agent systems, vector databases, model evaluation and monitoring, and MCP ecosystems
• Experience implementing production-grade AI governance and controls
• Advanced degree in Computer Science, Engineering, Data Science, AI, or related field
• Industry certifications in public cloud, data engineering, AI/ML, or security
• Experience in highly regulated industries such as financial services, healthcare, or insurance
• This position is not eligible for visa sponsorship

Demonstrates expertise in architecting cloud-native data and analytics platforms, with a strong focus on AI/ML solutions and data governance. Proven ability to lead enterprise-wide cloud transformation initiatives while ensuring compliance…