Senior AI Engineer - Evisort AI

Join the Evisort AI team at Workday, which powers Document Intelligence AI and Workday's CLM and Contract Intelligence offerings. Our mission is to change the way business deals get done. We build ground breaking AI technology that can read and understand contract language to make every part of the deal-making process from drafting, negotiating, reviewing, approving, or managing the contracts happen faster, better, with reduced risks. As a Senior AI Engineer, your primary focus will be building AI features and intelligent agents specifically for the Contract Lifecycle Management (CLM) domain, though you will also be expected to contribute to other areas of the product as needed. While AI development is the primary deliverable, this is first and foremost a software engineering role requiring deep expertise in backend architecture and distributed systems. You will be responsible for architecting advanced LLM-driven solutions and agentic workflows that are not only innovative but also enterprise-grade—meaning they are highly available, scalable, and secure. By leveraging Workday's rich datasets and computing resources, you will build the robust infrastructure necessary to deliver transformative AI value to our customers at scale.

Responsibilities

Building AI features and intelligent agents specifically for the Contract Lifecycle Management (CLM) domain; contributing to other areas of the product as needed; architecting advanced LLM-driven solutions and agentic workflows that are enterprise-grade, highly available, scalable, and secure; leveraging Workday's rich datasets and computing resources to build robust infrastructure for delivering AI value at scale; continuously evaluating and improving customer experience with AI agents; rigorously assessing agents' performance and user interactions; integrating AI agents into the broader Workday agents ecosystem.

Requirements

8+ years of professional software engineering experience, with a heavy emphasis on backend architecture, distributed systems, and a proven track record of shipping high-availability production code at scale. Strong fundamental software engineering skills (system design, scalability, and performance optimization) are a non-negotiable primary qualification for this role.; 3+ years of experience integrating AI capabilities (LLMs, Foundation Models) into enterprise products, framed within the context of robust software service extensions.; 1-2+ years building with AI orchestration frameworks (e.g., LangChain, LlamaIndex) with a focus on creating predictable, reliable, and maintainable agentic workflows.; 4+ years of proven experience leveraging cloud computing platforms (e.g., AWS, GCP, Azure) to deploy highly responsive, scalable systems.; 2+ years of hands-on experience deploying and operating services in containerized, cloud-native environments (Docker, Kubernetes), with exposure to infrastructure-as-code and GitOps tooling (e.g., Terraform, Helm, ArgoCD).

Nice to have

Bachelor’s degree in Computer Science, Software Engineering, or equivalent technical field.; Product-First AI Mindset: Deep focus on business value, user experience, and applying deep learning or large models directly to solve practical end-user challenges.; System Design & Reusability: Proven ability to architect robust application layers that wrap around AI models, establishing reusable patterns for system predictability, error handling, and seamless UX integration.; Experimentation & Evaluation: Skilled in rapid prototyping, benchmarking model outputs against product requirements, and setting up automated evaluation metrics (e.g., assessing retrieval quality and agentic behavior).; Hands-on experience with production observability and monitoring tooling (e.g., Prometheus/Grafana, OpenTelemetry, Sentry, Datadog) to debug, trace, and measure live systems; Familiarity with data persistence and async processing - relational databases and schema migrations (e.g., PostgreSQL), caching (e.g., Redis), and message/queue or task workflows (e.g., Celery, Kafka, SQS); A track record of writing well-tested, maintainable production code with attention to code quality, security scanning, and dependency hygiene (e.g., unit/integration tests, SonarQube, dependency tooling); Familiarity with full-stack development - building web UIs (e.g., React, TypeScript) and backend services/REST APIs in Python (e.g., FastAPI, Django); Technical Leadership & Mentorship: Proven track record of technically leading engineering workstreams, taking ownership of the development lifecycle, and mentoring junior-to-mid level engineers.; Collaborative Communication: Excellent interpersonal skills, with a knack for bridging the gap between product management, design, and foundational ML infrastructure teams.; Thrives in Ambiguity: Highly autonomous builder capable of taking open-ended product goals and breaking them down into concrete, scalable engineering realities.

Benefits

Workday Bonus Plan or role-specific commission/bonus; annual refresh stock grants; comprehensive benefits