AVP, Lead AI Engineer
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Reach the decision-maker — $5About the role
**OVERVIEW**
Drive AI engineering workstreams across the Audit\+ program, ensuring compliance of UW and Claims processing, automation of controls, as well as driving cost reduction.
**ROLE**
This role will work closely with regional teams to identify and build production grade foundational capabilities, platform those capabilities to enable rapid operationalization and scale out of Audit\+ AI capabilities. The primary focus is on end\-to\-end automation of controls across Claims, UW, Finance and Technology.
**FOCUS AREAS \& RESPONSIBILITIES**
* Develop the next generation of AI driven Audit\+ platforms and AI assets, including Agentic framework * Build scalable pipelines for data ingestion, feature engineering, model training, evaluation, and monitoring * Develop and integrate generative AI applications, including LLM\-based workflows, agents, and retrieval\-augmented generation (RAG) solutions * Ensure solutions meet security, privacy, compliance, and responsible AI standards * Optimize model performance, reliability, latency, and cost across the AI lifecycle * Platform capabilities for extending AI enablement to human\-lead operations in areas like QA, Training \| Operations for faster and efficient production and introduce efficiencies in distribution workflows * Enable sales analytics \| marketing with a foundational layer of AI with Consumer LLM as needed * Drive implementation and change management in collaboration with regional D\&A leads, business and technology partners * Work with the Consumer\+ Platform Engineering team to develop reusable Foundational AI Assets \| Applications to accelerate local deployments * Support Business Development by evangelizing our AI success stories to stakeholders and sponsors as needed * Enable the regional and local teams to leverage Global Consumer\+ platforms and be self\-sufficient **Operating Network:**
* Work closely with regional Data \& Analytics teams to identify opportunities and assist in implementation * Collaborate with Regional IT, GDO, Global Analytics, Ops for data \| infra \| integration related to implementation * Collaborate with teams to enforce responsible AI, model risk management, and AI governance
**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.*
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