Principal Agent Development Engineer - Agent Platform

Workday•Boulder, CO

1d•Hybrid

About The Position

The Agent Platform team delivers a new AI focused experience for Workday customers, and most importantly their employees. We are at the forefront of Workday’s AI & Agentic initiatives with the objective to deliver and integrate Agentic capabilities across the entire Workday platform, including the widespread adoption and AI powered Assist features, rapid creation and deployment of Workday-native AI Agents, and the delivery of Workday’s Agent System of Record. This role will specifically be part of the Agent Trust and Inspection team, with responsibilities including Agent Safety Scanning, Attestation, Observability, and enhancing the Customer Experience for Agent Management. This is a unique opportunity at the intersection of Agent development, operation, security, and identity. The Data & Frontier: Tackle unique challenges in Agentic AI utilizing Workday’s exclusive, high-integrity enterprise datasets. Impact at Scale: Your contributions will act as the crucial optimizer and gatekeeper of quality for products that reach 31 million global users. People-First Culture: We cultivate a culture that balances high-intensity innovation with a strong commitment to sustainable work-life integration. We are looking for creative, results-oriented, and collaborative Agent Development Engineers to help build and scale the next generation of our Agentic system. In this role as an Agent Development Engineer on the Agent Trust and Inspection team, you will significantly contribute to building trust in our AI agents by implementing essential guardrails and security features. This is an exciting chance to leverage and enhance various agent frameworks, adding crucial checks and balances to create practical, scalable, and reliable next-generation agentic products that streamline complex HR and Finance workflows for our worldwide customer base. If you are passionate about building real agentic products, tackling meaningful challenges, and working with a team dedicated to quality and craft, you will thrive in this role.

Requirements

Extensive Experience (12+ years) in software engineering or experience +equivalent educational background
Deep Expertise in Python: 5+ years writing modular, performant Python code and libraries.
Production ML/Autonomous Systems: 5+ years designing and implementing Machine Learning/autonomous systems in a production environment.
Familiarity with Agentic Frameworks: Exposure to frameworks such as Langchain, Langraph (preferred), CrewAI, and ADK.
End-to-End Agentic Architecture: Knowledge of the complete production architecture for modern Agentic systems, including MCP servers and AI gateways.
Agentic Design Patterns: Experience in the implementation of various Agentic Design Patterns.
Bachelor's degree in a computer related field or equivalent work experience

Nice To Haves

Familiarity with agentic coding tools such as Claude Code or Cursor
Experience building and operating SaaS products in cloud environments (AWS preferred)
Familiarity with the tradeoffs and architecture of modern distributed systems
Knowledge of software development best practices (DevOps, CI/CD, automated testing, observability)
Exposure to Amazon Bedrock/Google ADK or any other equivalent framework
Hands-on experience with containerization technologies (Docker, Kubernetes)
Proven success working within fast-paced, agile environments and cross-functional teams
Strong communication skills, with the ability to collaborate with both technical and non-technical partners

Responsibilities

Enhance and maintain features within our in-house/third-party agentic framework.
Build agents to automate workflows for the Agent Trust and Inspection team.
Develop and deploy adversarial agents and specialized sandbox environments to rigorously test and secure AI agents across the Workday ecosystem.
Work with cross-functional teams to embed real-time security guardrails into their agentic systems.
Collaborate in an iterative, team-first environment that values strong engineering practices and continuous learning.
Share knowledge, mentor teammates, and help raise the technical bar across the pod.
Evaluate the latest agentic technologies to determine their potential for enhancing our platform.