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The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

Serve as a liaison between business stakeholders and technical teams to elicit, document, and translate requirements; design and improve systems and processes; support implementations and post-release troubleshooting; mentor others; drive buy-vs-build decisions; facilitate training, data governance, and reporting needs; use Agile/Scrum/Waterfall methodologies and MS Copilot to create user stories and documentation while ensuring compliance with security and privacy requirements.

The Territory Sales Enablement Manager designs and manages programs that empower PEMCO's Community Agent channel, enhances agency capabilities, and drives growth through strategic initiatives and technology improvements.

The Digital Product Manager leads the strategy and development of AI-enabled digital products in the P&C insurance domain, ensuring customer experience and operational efficiency while aligning with business objectives and regulatory requirements.

Manage and optimize underwriting workflows and staffing to meet cycle times. Provide underwriting assistance during volume spikes, analyze data to improve processes, develop SOPs and training, ensure regulatory compliance, reduce manual work through technology, and communicate findings to stakeholders.

The Program Manager is responsible for developing and executing project plans, managing vendor relationships, and collaborating across teams to ensure successful program delivery at PEMCO.

Design and implement automated test frameworks and data validation utilities for enterprise data platforms. Validate data transformations, pipelines, lineage, and performance across Databricks, Snowflake, Spark, Hadoop and cloud environments. Integrate tests into CI/CD, perform white-box and performance testing, investigate production defects, and collaborate with Data Engineering, Analytics, and business stakeholders to ensure P&C insurance data quality and regulatory readiness.