Senior AI Evaluation Engineer (CICD & Platform)

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

We are seeking a Senior AI Evaluation Engineer (CI/CD & Platform) to own the continuous evaluation architecture, deployment pipeline infrastructure, and release gating for our enterprise AI Skills platform. In this role, you will build both the MLOps/CI-CD deployment pipelines and the automated eval harnesses that ensure all production AI skills execute accurately, remain schema-compliant, and run safely in live customer environments.

You will bridge the gap between AI skill development and production platform engineering—leveraging modern evaluation frameworks (e.g., LangSmith, Braintrust, DeepEval) alongside CI/CD pipelines to evaluate agent trajectories, test schema contracts, and certify every skill before deployment.

Key Responsibilities

• Continuous Evaluation:. Build tiered evaluation pipelines—separating instant static/schema checks for PR developer loops from comprehensive synthetic, multi-turn trajectory, and LLM-as-a-Judge eval suites for release promotion gates.

• CI/CD Quality Gates & MLOps Infrastructure: Architect and maintain CI/CD build pipelines (GitHub Actions, GitLab CI), skill registry versioning, and runner environments to enforce automated "pass/fail" release gates on every pull request.

• Deterministic Code & Schema Validation:. Develop synthetic data generation pipelines and automated red-teaming utilities that allow skill authors to instantly generate edge-case evaluation suites from raw API schemas and domain specifications.

• Benchmark Datasets & Regression Testing: Curate versioned golden datasets and execute continuous regression testing across base model upgrades, prompt changes, and security boundary checks.

• Production Observability: Ingest real-world production traces and failure logs back into benchmark datasets to continuously close test coverage gaps.

Basic Qualifications

• 4+ years of professional software engineering experience in Python building production-grade systems—with hands-on strength in EITHER CI/CD pipeline engineering OR AI evaluation methodology, plus working familiarity with the other.
• 2+ years designing, building, and operating test automation frameworks (pytest), CI/CD build pipelines (GitHub Actions, GitLab CI), or automated release gates.
• 1+ years of hands-on experience evaluating or building Generative AI applications (LLM tool-calling, agent workflows, or structured output parsing).
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Other Qualifications

• AI Evaluation Tooling: Direct experience with modern evaluation and observability frameworks (e.g., LangSmith, Braintrust, DeepEval, Promptfoo, Phoenix).
• Schema Contracts & API Validation: Strong knowledge of schema validation libraries (JSON Schema, Pydantic, OpenAPI) and API contract testing.
• Agentic Standards & MCP: Familiarity with the Model Context Protocol (MCP), tool-calling specifications, or agent execution harnesses.
• Static Code Analysis: Experience using schema validation frameworks (Pydantic, JSON Schema), linters, and test automation tooling to enforce agreed code contracts.
• AI Security & Governance: Understanding of core LLM failure modes (hallucinations, prompt injection, PII/PHI sanitization, RBAC boundaries).
• Quality & Testing Discipline: Strong engineering rigor around test coverage, dataset versioning, evaluator calibration metrics, and regression prevention in continuous deployment pipelines.
• Technical Communication & Leadership: Demonstrated ability to own problem domains end-to-end, collaborate closely with platform and product teams, and write clear technical documentation and architecture designs.

Listed below is the base salary range applicable to this position. Workday pay ranges (and the precise pay offered to the successful candidate) are based on a number of objective criteria such as relevant experience and skills, and educational qualifications, level of responsibility, demands of the role, work location and business need. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants awarded by Workday Inc. For more information regarding Workday’s comprehensive benefits, please click here.

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