Senior Software Engineer - AI Core (python)

Workday Workday · Enterprise · Vancouver, BC +1

Senior Software Engineer role focused on building and operating backend services for AI-powered applications and agentic systems within an enterprise AI platform. Responsibilities include developing production-grade services, designing APIs, building data pipelines, applying distributed systems principles, and ensuring security and compliance. Requires strong Python expertise, experience with cloud platforms, and understanding of distributed systems.

What you'd actually do

  1. Work closely with machine learning engineers to write and maintain production-grade backend services that power AI-driven capabilities and agent applications
  2. Design and implement APIs and service integrations that enable AI capabilities to be consumed across Workday products and platforms
  3. Build and operate data ingestion and ETL pipelines that support AI application workflows
  4. Apply distributed systems principles in production to address scalability, concurrency, fault tolerance, and performance challenges
  5. Ensure systems meet enterprise requirements for security, privacy, robustness, and compliance

Skills

Required

  • 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 and ability to apply them in a Python context
  • Proficiency with advanced Python concepts, such as asynchronous and concurrent programming, generators, and higher-order abstractions
  • Ability to write clean, testable, and well-structured code, with high standards for clarity, aesthetics, and long-term maintainability
  • 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
  • Ability to design and build well-defined, stable APIs and service interfaces for consumption by other teams and systems
  • Proficiency with cloud and container platforms, including containerized workloads and orchestration systems (e.g., AWS or GCP, Docker, Kubernetes)

Nice to have

  • AI-powered software
  • agentic reasoning
  • enterprise-scale systems
  • AI platform capabilities
  • agent applications
  • AI-driven capabilities
  • agent applications
  • AI capabilities

What the JD emphasized

  • production-grade backend services
  • agent applications
  • AI capabilities
  • data ingestion and ETL pipelines
  • distributed systems principles
  • scalability, concurrency, fault tolerance, and performance challenges
  • security, privacy, robustness, and compliance
  • Python expertise
  • architecting, building, and scaling secure, robust, and efficient software systems
  • Python development
  • object-oriented design principles
  • advanced Python concepts
  • asynchronous and concurrent programming
  • clean, testable, and well-structured code
  • Deep systems knowledge
  • Unix/Linux environments
  • command-line tooling
  • networking fundamentals
  • distributed systems concepts
  • concurrency, fault tolerance, and performance tradeoffs
  • design and build well-defined, stable APIs
  • cloud and container platforms
  • containerized workloads and orchestration systems
  • AWS or GCP, Docker, Kubernetes

Other signals

  • AI-powered software
  • AI platform
  • agentic reasoning
  • enterprise-scale systems
  • AI platform capabilities
  • agent applications
  • AI-driven capabilities
  • agent applications
  • AI capabilities