The Architecture & AI (AAI) organization is a dynamic and evolving team that is spearheading Workday’s growth through trusted data excellence, innovation, and architectural thought leadership. Equipped with an array of skills in data & AI platforms and architecture, data science, engineering, machine learning and AI strategy & product management, this team orchestrates the flow of data across our growing company while ensuring data accessibility, accuracy, and security With a relentless focus on innovation and efficiency, Workmates in AAI enable the transformation of complex data sets into actionable insights that fuel strategic decisions and position Workday at the forefront of the technology industry We are seeking a Principal AI Engineer to own the technical path that carries internally built AI agents from prototype to enterprise-grade production on Workday’s Databricks and AWS estate. This is a hands-on engineering role at the intersection of AI applications, data, identity and platform You will design the architecture and work in code to build the reference implementations and evaluation harnesses that business-built applications are re-architected onto, and hold the technical bar as those applications move into production

Production readiness standards and automated enforcement: Define and enforce what production-ready means for an AI application at Workday — exit criteria against BT’s existing security, code, testing and documentation gates, plus the evaluation sets, graders and regression suites that run in the deployment pipeline to prove those criteria are met, drawing on representative data, production signals and human review

Architecture and paved-road assets: Own the architecture patterns for AI applications across the Databricks and AWS stacks, and build and maintain the reference implementations and deployment templates for each recurring pattern, so a team building a known pattern inherits correct identity,



data access and logging posture by construction

Hands-on engineering: Work in code with the current stack; AWS Bedrock and AgentCore, Databricks Agent Bricks and Unity Catalog — to build prototypes, tool and system integrations, and to re-architect AI-generated applications into services that can hold a production state

Technical diagnosis and resolution: Diagnose complex implementation challenges in non-deterministic systems, reproduce failures, bisect regressions across model version, prompt, retrieval index and tool schema, trace latency and token cost across multi-step agent runs, test hypotheses, and drive blockers to resolution with platform, data, security and SRE owners

Design review and transition to operations: Run design and readiness reviews with platform, data, security and SRE partners, and own the handoff so no application enters production without an operator, a patch path and a rollback

Business engagement: Work with the business teams building these applications to translate what they need into platform and data design, and translate platform constraints back into decisions they can act on, including the decision not to proceed

Cross-functional technical leadership: Be the technical counterpart business owners consult before building, and carry direction across partner functions on influence rather than mandate

8+ years of experience in Data & AI application development in a Python, IaC and CI/CD; production workplace

8+ years of up-to-date data stack experience, ie; Databricks, AWS, Snowflake, GCP, or comparable technologies

6+ years of professional experience with LLM applications in a major cloud AI-native stack

Excellent verbal and written communication skills

Work with business counterparts and carry direction across partner functions on influence

Open to 50% reporting to our Toronto office

Ability to work in alignment with business teams to build applications and translate platform constraints back into decisions

📌 Principal Engineer (AI Production Readiness) (Toronto)
🏢 Workday
📍 Toronto