Principal Engineer, Workday
AI Production Readiness
CA$149.3-223.9k
More information about location
Enterprise AI platform for managing HR, finance & IT
Be an early applicant
Enterprise AI platform for managing HR, finance & IT
1001+ employees
Be an early applicant
CA$149.3-223.9k
More information about location
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 8+ years of experience in Data & AI application development in a Python, IaC and CI/CD; production environment
- 8+ years of modern 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
- Ability to work in alignment with business teams to build applications and translate platform constraints back into decisions
- Work with business counterparts and carry direction across partner functions on influence
- Open to 50% reporting to our Toronto office
What the job involves
- 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
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, Workday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & CEO)Annel began their career at Morgan Stanley as a Corporate Finance Analyst. They then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005.
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