Senior Software Development Engineer - AI Core

Workday•Vancouver, BC

1d•Hybrid

About The Position

Workday is seeking a Senior Software Development Engineer for their AI Core team, which is at the forefront of agentic AI. This team builds the foundational systems that enable autonomous agents to reason, act, and deliver value across Workday's HR and Finance products. A key focus is the retrieval layer, developing systems that help agents access the right information quickly and accurately for enterprise workflows. The AI Core team addresses complex challenges at the intersection of machine learning and large-scale enterprise systems for information retrieval and recommendation use cases. In this role, you will be responsible for designing, building, and operating the software systems that host, run, and scale AI-powered agentic applications at Workday. You will develop agentic tooling for both unstructured and structured information retrieval across Workday’s extensive datasets. This includes designing and implementing production-grade services, APIs, and ETL pipelines for the ML RAG platform, applying distributed systems principles to ensure scalability, fault tolerance, and performance, automating CI/CD and testing, and ensuring systems meet enterprise requirements for security, privacy, robustness, and compliance. You will own services throughout their entire lifecycle, from deployment to ongoing operational improvements.

Requirements

8+ years of professional software development experience, including architecting, building, and scaling secure, robust, and efficient software systems
5+ years of experience with Python development
Bachelor’s degree in Computer Science, Engineering, or related discipline, or equivalent practical experience
Understanding of object-oriented design principles
Proficiency with advanced Python concepts such as asynchronous and concurrent programming, generators, higher-order abstractions, Pydantic and Pyspark
Deep systems knowledge, including comfort operating in and debugging Unix/Linux environments, fluency with command-line tooling, and understanding of practical networking fundamentals
Understanding of distributed systems concepts, including concurrency, fault tolerance, and performance tradeoffs
Proficiency with cloud and container platforms, including containerized workloads and orchestration systems (e.g., AWS or GCP, Docker, Kubernetes)
Ability to collaborate effectively across teams, working closely with other engineers while maintaining independent execution
Ownership mindset, able to take responsibility for a work area and deliver high-quality, reliable systems
Ability to mentor and coach other engineers, promoting best practices and raising the engineering bar
Architectural thinking skills, with the ability to contribute meaningful ideas and practical solutions in design and architecture discussions
Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders

Nice To Haves

Preferred prior experience with building scalable services and pipelines for ML use cases in Production

Responsibilities

Design and implement production-grade services, APIs, and ETL pipelines in the ML RAG platform, which is consumed by numerous AI-driven Workday products and high-priority agents
Apply distributed systems principles in production to address scalability, concurrency, fault tolerance, and performance challenges
Automate CI/CD and testing workflows, and proactively look for ways to improve developer experience
Ensure systems meet enterprise requirements for security, privacy, robustness, and compliance
Own services through their full lifecycle, including deployment, monitoring, debugging, and ongoing operational improvements