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Lead and scale the company’s data governance program by defining operating models, standards, and lifecycle controls. Partner with data owners, stewards, and the Data Office to improve data quality, integrity, access, cataloging, lineage, and metadata management. Develop training, resources, and KPIs to strengthen data literacy and a data-centric culture while translating governance risks into business impacts for leadership.

Partners with engineering and technical leaders to run full-cycle recruiting, build talent pipelines, advise on market and compensation trends, improve hiring processes, and maintain ATS data integrity while mentoring teammates.

Design, build, and maintain web applications and microservices using Go and React. Drive technical decisions, mentor engineers, improve CI/CD, testing (unit, integration, E2E) and observability, diagnose performance/security issues, and collaborate with product and design to deliver reliable, well-tested solutions.

Lead full-cycle recruiting for Go-to-Market roles (Sales, Customer Success, Solutions Engineering, etc.). Partner with hiring managers to design structured interviews, build talent pipelines, source candidates, negotiate offers, and support onboarding. Use recruiting metrics and market insights to drive hiring decisions and improve processes while promoting inclusive hiring practices.

Design, harden, deploy, and operate LLM-powered applications and agents on a governed GCP platform. Build integrations, retrieval pipelines, dashboards, monitoring, CI/CD, secrets management, and automated maintenance while partnering with business stakeholders to move proofs-of-concept into production.

Join the IT AI Automation team to build and harden micro-apps and AI integrations on a governed GCP platform. Contribute to bug fixes, small features, code and design reviews, apply foundational security and software practices, monitor applications, and use AI tools to support development, testing, and documentation while learning from senior engineers.

Lead intake, roadmap, and governance for an AI automation/platform team that hardens and ships business-built AI apps to production. Define security, MLOps, responsible-AI standards, evaluate vendor tooling, manage stakeholder communication, measure adoption and costs, and enable business units for safe, scalable AI deployments on a shared GCP platform.

Design, build, and optimize BigQuery-based data models and pipelines on Google Cloud. Implement SQL procedures, manage storage/partitioning, ensure data quality, collaborate with data scientists and engineers, document designs, and improve ETL and reporting workflows.

Lead and execute agency adoption and engagement strategy across Applied's commercial lines portfolio in North America. Build scalable operating models, drive executive-level agency relationships, orchestrate cross-functional teams, and convert product availability into sustained day-to-day usage and bound premium. Own major migrations, digital adoption motions, change management, and measurable market outcomes.