Jobs at Workday

Build and operate scalable full-stack features for Evisort’s AI-driven contract management platform. Collaborate with engineering, data science, product, and design teams; contribute to product strategy and roadmap; own functionality from development through production; apply strong engineering practices including DevOps, CI/CD, testing, observability, containerization, and distributed-systems design. Participate in an agile, collaborative culture through mentorship, knowledge sharing, and cross-functional problem solving.

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.

Drive customer outcomes and measurable value realization for specialized AI-enabled SaaS products. Build success plans, guide adoption, quantify ROI, identify expansion and churn signals through product data, support AI change management and responsible governance, and create scalable playbooks and enablement for Customer Success teams. Partner cross-functionally with Product, Services, Support, Digital CS, and customers in a fast-moving environment.

Lead design and delivery of production-grade agentic AI systems: architect LLM integration, orchestration, and routing; ensure reliability, low latency, cost efficiency, and Responsible AI guardrails; translate AI capabilities into enterprise product value and mentor cross-functional teams.

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 concurrent Workday Financials, HCM, and Payroll implementations throughout the full delivery lifecycle. Responsibilities include project planning, staffing, budgeting, performance measurement, risk and issue management, executive steering committee presentations, customer relationship management, change orders, team mentoring, sales-cycle support, and transition to product support. The role also identifies additional service opportunities and ensures customers adopt best practices and can serve as references.

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.

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.

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 production-grade ML systems for LLM-powered agents: implement RAG pipelines, orchestration, deployment, monitoring, and continuous improvement at scale while partnering with product, software, and data teams.

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.

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.

Lead overall success for an assigned portfolio of Workday subscribers: build executive relationships, orchestrate cross-functional resources, drive adoption and subscription retention/growth, and deliver exceptional customer experiences while supporting deployments and ongoing production.

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 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.

As a Machine Learning Engineer, you will develop user experiences using LLMs and predictive analysis, deliver ML solutions, and ensure continuous improvement in AI products at scale.

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.

Enable strategic GSI and ecosystem partners on Workday HCM and agentic AI: develop functional playbooks, translate roadmap into partner-ready narratives, advise on competitive positioning and regulatory risks, support demo readiness, and act as a first-line functional expert for partner HCM teams.

The role involves architecting AI solutions, optimizing ML systems, and deploying advanced retrieval frameworks. Engineers will lead ML lifecycle from research to production, collaborating across teams to build AI-first products.

As a Full Stack Software Engineer, you will develop and deliver full stack features for AI agents integrated into HR and financial workflows, collaborating within a cross-functional team to ensure quality and performance from development to production.