Jobs at Workday

Lead the architecture, orchestration, and product integration of production-grade AI agents. Design scalable systems integrating LLMs into enterprise applications, build multi-agent and RAG workflows, optimize latency and cost, and implement responsible AI governance, privacy, security, evaluation, and reliability controls. Provide technical leadership across cross-functional teams while translating AI capabilities into practical business products.

Demonstrates Workday Financials to prospects and customers throughout the sales cycle. Delivers technical presentations, product demonstrations, workshops, seminars, discovery sessions, proof-of-concept builds, and RFI responses. Partners with sales to qualify opportunities, understand financial processes, address customer questions, and support deal closure. Requires accounting and financial management expertise, cloud ERP experience, strong executive communication skills, bilingual French and English fluency, and 50% travel.

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.

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.

Leads a specialized enterprise sales team selling platform, data, analytics, AI, and extensibility solutions to CIO and CTO organizations. Responsibilities include coaching account executives, managing complex $500K+ ARR sales cycles, overseeing statements of work and technology roadmaps, forecasting revenue, modeling business performance, and coordinating co-selling with AWS, GCP, and global system integrators.

Lead complex enterprise sales cycles for Workday platform, data, analytics, AI, and extensibility solutions. Build executive relationships with CIOs and CTOs, develop account strategies and pipeline, translate technical priorities into business value, and close large multi-stakeholder deals. Coordinate presales, product, customer success, partners, and core account teams while advancing cloud, data, AI, integration, security, and enterprise transformation opportunities.

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.

As a Software Engineer on the Pipedream team, you'll enhance Pipedream Connect's capabilities, develop APIs, and work with a diverse tech stack, including Go and Node.js, to deliver impactful integrations for customers.

Leads vision, strategy, and roadmap execution for Workday’s AI-powered Contract Intelligence and Analytics portfolio. Partners with engineering, data science, design, marketing, customers, and executives to develop generative and predictive AI products, define requirements, analyze markets, establish monetization strategies, and deliver enterprise SaaS solutions at scale.

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.

Lead technical design and development of Workday’s large-scale AI model-serving platform. Build and operate distributed systems for traditional ML models and LLMs, optimize Kubernetes and GPU infrastructure, improve CI pipelines, troubleshoot production issues, establish observability, review code, document architecture, and mentor engineers while ensuring platform scalability, reliability, performance, and security.

Principal Software Engineer responsible for evolving Evisort’s AI-driven contract management platform. The role involves collaborating across engineering, data science, product, and design; shaping technical strategy and architecture; building scalable SaaS solutions; owning systems from development through production; mentoring teammates; and applying distributed systems, cloud, DevOps, containerization, testing, and observability practices.

Design and build production-grade ML systems and LLM-powered agent frameworks (RAG, orchestration, evaluation). Own model lifecycle from data strategy to deployment, monitoring, and continuous improvement, partnering with software engineers, product managers, and data scientists to integrate scalable, observable, and enterprise-ready agents.

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.