AVP, Lead AI Engineer

Candidate Profile: Technical Skills • Strong hands-on coding ability in Python plus at least one additional language (TypeScript, Go, or Java); disciplined about clean code, design docs, and code review. • Deep knowledge of modern LLM tooling and techniques: Hugging Face Transformers, prompt engineering, post-training/fine-tuning pipelines, retrieval-augmented generation (RAG), and agentic AI frameworks. • Experience with inference optimization and high-throughput serving frameworks. • Proven experience shipping and operating high-scale services on Docker/Kubernetes with CI/CD pipelines (GitHub Actions, Jenkins, or similar). • Experience with event-stream/service-integration technologies (e.g., Kafka) and building resilient, observable production systems (SLOs for latency, error rate, availability). • Experience building end-to-end ML pipelines: data ingestion, feature engineering, model training, evaluation, and monitoring. • Experience integrating AI/LLM services into user-facing products (APIs, SDKs, real-time UX features). Governance, Risk & Compliance • Working knowledge of responsible AI practices, model risk management, and AI governance frameworks. • Experience Ensuring AI solutions meet security, privacy, and regulatory compliance standards, particularly in audit, underwriting, or claims-adjacent contexts. Leadership & Collaboration • Ability to architect and own robust, scalable engineering solutions while remaining hands-on with code. • Experience partnering cross-functionally with regional Data & Analytics teams, IT, GDO/Ops, front-end, and DevOps stakeholders to drive implementation and change management. • Ability to represent technical architecture, trade-offs, and AI risk to both engineering leaders and non-technical executives with clarity and confidence. Attributes • Outstanding written and verbal communication across technical and executive audiences. • Bias for action and comfort making high-impact decisions under uncertainty. • Ability to drive KPI/OKR-based delivery in an iterative, sprint-based environment. Chubb Canada does not use artificial intelligence (AI) tools to assess, screen, or select applicants.

At Chubb we are committed to providing equal employment opportunities to all employees and applicants. It is our policy to provide equal employment opportunities to employees and applicants based on job-related qualifications and ability to perform a job. If you require an accommodation during the hiring process or upon hire, please inform Human Resources. If a selected applicant requests accommodation during the recruitment process, Chubb will consult with the applicant in order to provide suitable accommodation that takes into account the applicant’s accessibility needs.