Jobs at Workday

Design and build production-grade AI agents integrated into Workday’s enterprise platform. Develop agentic workflows, orchestration architectures, and scalable backend systems; integrate and govern LLMs over sensitive HR and financial data; implement privacy, security, explainability, evaluation, and reliability guardrails; optimize latency, cost, and context usage; lead engineering workstreams and mentor engineers.

Develop and deploy scalable AI products using LLMs, knowledge graphs, personalization, and predictive analysis. Build reliable AI orchestration workflows, backend services, data pipelines, and cloud-native infrastructure. Architect maintainable systems, evaluate model performance, implement observability and experimentation, and deliver secure, high-availability software. Collaborate with product, design, and ML infrastructure teams while mentoring engineers and translating ambiguous product goals into customer-focused solutions.

Provides technical Workday integration consulting to customers after go-live. Responsibilities include researching customer questions, troubleshooting and optimizing configurations, delivering demonstrations, presentations, workshops, feature adoption guidance, configuration reviews, integration optimization, and feature deployments. The consultant serves as a trusted Workday advisor, maintains certifications and product expertise, supports customer decision-making, and helps create programs that improve feature adoption. Travel may be required up to 20%.

Develop and deploy scalable AI agents for HR and Finance workflows. Responsibilities include implementing machine learning frameworks, integrating LLMs, RAG, agent orchestration, and cloud services, supporting the full AI system lifecycle, and establishing monitoring and feedback loops. The role partners with engineering, product, data science, vendors, and cloud providers to deliver reliable production machine learning solutions and may lead or mentor ML engineering teams.

Designs and operates cloud infrastructure, distributed systems, CI/CD pipelines, Kubernetes and EKS environments for a high-scale SaaS platform. Responsibilities include infrastructure automation, capacity planning, performance optimization, monitoring, alerting, security, infrastructure as code, developer productivity tooling, and maintaining highly available systems. The role collaborates closely with developers and platform engineers to deploy reliable, scalable services across AWS and GCP.

Build and operate scalable full-stack features for Evisort’s AI-driven contract management platform. Collaborate with engineering, data science, product, and design teams to deliver user-centric SaaS solutions. Own functional areas from development through production, apply strong engineering and DevOps practices, contribute to roadmap and architecture decisions, mentor teammates, and translate complex problems into clear solutions in an agile environment.

Lead the vision, strategy, roadmap, and execution for Workday Evisort’s Contract Intelligence and Analytics portfolio. Partner with engineering, data science, design, marketing, customers, and domain experts to build and launch generative and predictive AI products. Define requirements, evaluate market opportunities, develop monetization strategies, track product metrics, and deliver contract intelligence capabilities for enterprise customers.

Build and operate full-stack features powering AI agents within HR and Finance workflows. Own user-facing experiences and backend services through production, collaborate with machine learning engineers and product teams, apply distributed systems and cloud engineering practices, and mentor teammates. The role requires Python web development, relational databases, SaaS experience, containerization, DevOps, testing, and observability expertise.

Serve as the analytics and data science partner for Workday Data Cloud, connecting demand, sales pipeline, product usage, and consumption-based pricing. Investigate ambiguous business questions, derive decision-ready insights, create visualizations and executive narratives, and advise senior stakeholders. Build curated data assets, improve data connections and pipelines, address instrumentation gaps, and collaborate with Product, Engineering, and GTM teams to support strategic growth and data-driven decision-making.

Build and maintain front-end features for an AI-driven contract management SaaS. Collaborate with engineers, data scientists, product, and design; own functional areas from development to production; mentor teammates; apply modern dev practices to deliver scalable, user-centric solutions.

Lead technical direction and implementation of a large-scale AI model serving platform. Design, build, and operate distributed systems (Ray/Ray Serve), ensure scalability, reliability, monitoring (Prometheus), CI pipeline robustness, and evolve the production model registry while collaborating with ML engineers and stakeholders.

Lead development of scalable AI platforms and production machine learning services. Design agentic AI capabilities including tool calling, multi-agent systems, planning, reasoning, and human-in-the-loop workflows. Build Python services and Kubernetes-based ML infrastructure, multi-tenant runtimes, data pipelines, and cloud deployments. Apply MLOps, automation, observability, CI/CD, testing, and distributed-systems practices while collaborating with engineers, researchers, and cross-functional teams.

Lead the design, development, scaling, and operation of Workday’s AI model-serving platform. Build distributed systems for traditional machine learning models and large language models, optimize Kubernetes and GPU infrastructure, improve reliability and observability, troubleshoot production issues, maintain CI pipelines, review code, write technical documentation, and mentor engineers while driving architectural decisions.

Serve as the Finance-focused functional expert enabling GSI and ecosystem partners on Workday Financials and agentic AI. Develop playbooks, translate roadmap into outcomes, support partner positioning, demos, competitive messaging, and regulatory/risk considerations for finance AI use cases. Collaborate with solution architecture, solution consulting, and partner teams to ensure partner readiness, demo fidelity, and go-to-market success.

Develop and deploy production machine learning products for financial workflow automation. Responsibilities include designing ML features, training models, building APIs and scalable services, evaluating model performance, ensuring observability, and applying LLMs, RAG, natural language understanding, and autonomous agents to business documents and workflows. The role also requires technical leadership and mentoring junior engineers.

As a Principal Machine Learning Engineer, you'll design and implement core ML systems for AI agents, collaborating with cross-functional teams and overseeing the full lifecycle of products from data strategy to deployment.

Manage the vision, strategy, and roadmap for Contract Intelligence AI products. Collaborate with teams to define requirements and market strategies, ensuring delivery of generative AI solutions.

As a Senior Backend Software Engineer, you'll enhance the AI-driven contract management platform by collaborating with teams, optimizing code, and ensuring platform performance through API development and monitoring strategies.

Design and build core ML systems for production-grade AI agents, owning model, agent logic, orchestration, deployment, monitoring, and continuous improvement. Implement RAG pipelines, workflow orchestration, evaluation and feedback loops, and ensure scalable, observable, explainable, enterprise-ready solutions in collaboration with product, software, and data teams.

Design, build, and deploy scalable AI features using LLMs, knowledge graphs, and orchestration frameworks. Integrate models into enterprise products, optimize performance and latency, and manage model lifecycle, observability, and cloud-native deployments. Collaborate cross-functionally, lead engineering workstreams, and maintain high quality, secure production services.