Senior AI Engineer

Workday•Vancouver, BC

9d•CA$180,200 - CA$270,200•Hybrid

About The Position

Workday is seeking a Senior AI Engineer to join their Agent Factory team. This role involves designing and building core ML systems for Workday's next generation of AI agents. The engineer will work within a small, senior, cross-functional pod, owning the integration of models, agent logic, and orchestration layers throughout the full lifecycle. This includes problem framing, data strategy, deployment, monitoring, and continuous improvement. The role focuses on implementing and evolving frameworks for LLM-powered agents, such as RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring scalability, observability, and enterprise readiness. It sits at the intersection of ML and platform engineering, requiring close collaboration with software engineers, product managers, and data scientists to integrate agents into the Workday stack. The engineer will stay current with emerging techniques in agentic architectures and apply strong engineering judgment to create reliable, explainable systems operating at global scale.

Requirements

7+ years experience as a member of an AI engineer, data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
4+ years of professional experience in building services to host machine learning models in production at scale
2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
4+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)
Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement
Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent

Nice To Haves

Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
Professional experience in independently solving ambiguous, open-ended problems and technically leading teams
Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders

Responsibilities

Design and build the core ML systems behind Workday’s next generation of AI agents.
Own how models, agent logic, and orchestration layers come together in production across the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement.
Implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops.
Ensure solutions are scalable, observable, and enterprise-ready.
Partner closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack.
Stay hands-on with emerging techniques in agentic architectures.
Apply strong engineering judgment to turn emerging techniques into systems that are reliable, explainable, and built to operate at global scale.
Lead, mentor, and/or manage ML Engineering teams.
Take ownership of development lifecycle and sprint planning.
Foster a culture of collaboration, transparency, innovation, and continuous improvement.