ai engineer in reinsurance

Pacific Life Re operates in the reinsurance industry and develops solutions for a regulated financial services environment.

• Design, build, and pilot AI-enabled solutions for PL Re business problems through experimentation and rapid prototyping;
• Translate business use cases into secure, scalable, cloud-hosted AI solutions aligned with enterprise standards;
• Deliver hands-on full-stack and AI development for solutions that may transition into strategic or BAU platforms;
• Design prototypes with consideration for scalability, operability, data governance, and integration pathways;
• Research and evaluate emerging AI approaches, tools, and techniques;
• Apply AI research insights to experimentation, solution design, and technical direction;
• Ensure adherence to PL Technology engineering standards, architecture principles, and security controls;
• Partner with Enterprise Architecture and Information Security on governance and regulatory expectations;
• Ensure solutions respect data ownership, lineage, residency, and PII handling principles;
• Apply approved integration patterns when accessing platforms, data products, or external services;
• Share cloud and AI engineering insights, patterns, and lessons learned with the Global Experience Analysis engineering team;
• Bridge Business & AI experimentation and wider PL Re technology capabilities to accelerate AI adoption;
• Contribute to high-level logical and cloud architecture designs for AI use cases progressing beyond experimentation;
• Align AI solutions with Architecture Governance, PL Re target architectures, approved platforms, integration patterns, and data architecture principles;
• Identify architectural impacts, dependencies, and technical debt risks arising from AI experimentation;
• Lead through influence by setting technical direction and standards without formal authority.

• Demonstrable experience designing, building, and piloting AI-enabled solutions through rapid prototyping and experimentation with business stakeholders;
• Strong hands-on development experience with Python, APIs, and modern application architectures;
• Experience translating business problems into practical, secure, scalable solutions aligned with enterprise standards;
• Experience evaluating and applying AI technologies in regulated or risk-aware environments;
• Strong engineering judgement, balancing innovation with operational readiness and control;
• Strong ownership and accountability for delivery outcomes;
• Clear, confident communication with technical and non-technical stakeholders;
• Risk-aware, quality-driven mindset suited to a regulated financial services environment;
• Nice to have: AI, data, and analytics platforms on AWS or Azure, managed AI or foundation model services, actuarial or insurance technology environments, DevOps / DevSecOps and enterprise CI/CD pipelines, enterprise architecture and design governance, OpenAI, AWS Bedrock, Claude, Llama, Azure AI Foundry, Copilot Studio, GitHub Copilot, or similar ecosystems.

• 25 Days of annual leave with the option to buy or sell additional days;
• Adoption and fertility leave;
• Enhanced parental leave;
• Comprehensive private insurance coverage for employees and dependents;
• Group Life Insurance coverage of 9x basic annual salary;
• Group Income Protection of up to 75% of basic annual salary;
• Optical benefits;
• 15% Combined employee and employer savings and retirement contributions;
• Subsidized gym membership;
• Access to an Employee Assistance Program;
• Cycle to Work and Electric Car Salary Sacrifice Scheme;
• Time off for volunteering;
• Charitable matching of employee donations;
• Team-building days, social activities, and wellbeing initiatives;
• Reasonable adjustments are available during the recruitment process for applicants with disabilities.