AI Engineer

Job Description

Senior AI Engineer – Evisort AI | Workday

The Tone:
This is a full-time role at Workday, located in Vancouver, British Columbia, Canada (hybrid). Workday is a Fortune 500 company and a leading AI platform for managing people, money, and agents. The Evisort AI team, functioning as a startup within Workday, builds groundbreaking AI technology to understand contract language, making deal-making processes faster, better, and with reduced risks. This role is crucial for developing advanced AI solutions using LLMs and knowledge graphs, delivering transformative value across Workday’s product ecosystem to a customer base of over 70 million users.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Hybrid – Vancouver, British Columbia, Canada
• Pay: $169000–$253000 CAD yearly
• Team: Evisort AI team, functions as a startup within Workday
• Mission: Develop groundbreaking AI technology to read and understand contract language, accelerating deal-making processes and reducing risks for customers.
• Tech Stack: LangChain, LlamaIndex, AWS, GCP, Azure, Docker, Kubernetes, Terraform, Helm, ArgoCD, Prometheus, Grafana, OpenTelemetry, Sentry, Datadog, LaunchDarkly, PostgreSQL, Redis, Celery, Kafka, SQS, SonarQube, React, TypeScript, Python, FastAPI, Django

What You’ll Actually Do
• Develop: Help develop tailored user experiences leveraging advanced LLMs, Knowledge Graphs, personalization, and predictive analysis capabilities.
• Collaborate: Partner with other engineers to deliver AI solutions across Workday’s extensive product ecosystem.
• Utilize: Implement software and data engineering stacks to enable the training, deployment, and lifecycle management of various AI pipelines.
• Deploy: Develop and deploy new products at scale, leveraging Workday’s vast computing resources on rich datasets to deliver transformative customer value.
• Improve: Contribute to feature and service development with a continuous improvement approach, focusing on quality, scale, and security.

The Must-Haves
• Background: Senior-level professional with a Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field, possessing strong fundamental software engineering skills in system design, scalability, and performance optimization.
• Experience: 8+ years of professional software engineering experience with a heavy emphasis on backend architecture and distributed systems; 3+ years integrating AI capabilities (LLMs, Foundation Models) into enterprise products; 1-2+ years building with AI orchestration frameworks (e.g., LangChain, LlamaIndex); 4+ years leveraging cloud computing platforms (e.g., AWS, GCP, Azure); and 2+ years deploying and operating services in containerized, cloud-native environments (Docker, Kubernetes).
• Skills: Robust system design, scalability, performance optimization, AI integration (LLMs, Foundation Models), AI orchestration frameworks, cloud computing platforms, containerization, infrastructure-as-code, and a product-first AI mindset.
• Bonus: Master’s degree preferred, proven ability to architect reusable application layers, skilled in rapid prototyping and automated evaluation metrics, hands-on experience with production observability and monitoring tooling, familiarity with data persistence and async processing, track record of writing well-tested production code, familiarity with full-stack development, and technical leadership and mentorship experience.