Principal AI Engineer (LLM/RAG): Designing and building production-grade ML systems for Workday’s next generation of intelligent agents with an accent on model integration, agent logic, orchestration, and end-to-end lifecycle ownership. Focus on building scalable RAG pipelines, evaluation and feedback loops, deploying observable model services, and solving reliability and explainability challenges at global scale.
Location: Vancouver, British Columbia, Canada. Hybrid Flex Work requires spending at least 50% of each quarter in the office or in the field with customers, prospects, and partners.
Base salary: 188,000–282,000 CAD per year, with possible bonus, commission or annual refresh stock grants.
Company
hirify.global is a Fortune 500 company providing an AI platform for managing people, money, and business workflows.
What you will do
Design and build core machine learning systems for production AI agents.
Develop frameworks for LLM-powered agents, including RAG pipelines and workflow orchestration.
Own the lifecycle from problem framing and data strategy through deployment, monitoring, evaluation, and continuous improvement.
Build scalable, observable, reliable, and explainable agent systems integrated into the hirify.global platform.
Partner with software engineers, product managers, and data scientists in a senior cross-functional pod.
Provide technical leadership while applying emerging techniques in agentic architectures.
Requirements
10+ years of experience building applied machine learning products at scale across research, design, implementation, production, and evaluation.
4+ years of professional experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow.
6+ years of experience building services that host machine learning models in production at scale.
3+ years of experience with large language models, text generation models, and/or graph neural networks.
6+ years of experience with cloud computing platforms such as AWS or GCP.
Experience leading, mentoring, or managing ML engineering teams, plus a bachelor’s degree in engineering, computer science, physics, mathematics, or an equivalent field.
Nice to have
Master’s degree or PhD.
Deep knowledge of statistical analysis, supervised and unsupervised learning, and natural language processing for information retrieval or recommendation systems.
Experience solving ambiguous, open-ended problems and technically leading teams.
Culture & Benefits
Flexible hybrid work combining office and remote time.
Opportunity to work on production-grade AI used by millions of people.
Bonus, commission or role-specific bonus eligibility and annual refresh stock grants may be available.
Reasonable accommodations are available during the application process.
Equal opportunity employment with consideration for qualified applicants with disabilities and protected veterans.
Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →