Top Tech Jobs & Startup Jobs

Design, build, operate, and scale large distributed web services and tooling on private cloud and public clouds. Lead SRE/DevOps activities including automation, performance, security, on-call support, CI/CD optimization, and mentoring engineers to improve reliability and deployment pipelines.

Design and build core ML systems for AI agents, managing the lifecycle from problem framing to deployment, ensuring solutions are scalable and enterprise-ready.

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.

Collaborate with product and QA to design and develop metadata-driven, object-oriented web/SaaS applications. Build maintainable code, optimize performance, troubleshoot customer issues, and mentor teammates through reviews and pair programming.

Drive net-new revenue by targeting and closing large enterprise accounts. Develop account and territory strategies, coordinate with pre-sales, sell Workday cloud ERP/HCM/financial solutions, negotiate with C-suite executives, manage long deal cycles, and maintain accurate pipeline and forecast data.

Lead discovery and delivery for developer productivity tooling: define roadmap, translate developer pain points into specifications, prioritize features, collaborate with engineering and automation teams, and deliver product demos and stakeholder communications within an Agile Scrum environment.

Design and develop metadata-driven web/SaaS business applications using object-oriented languages. Collaborate with product and QA, optimize performance, troubleshoot customer issues, lead technical design, and mentor engineers. Support U.S. federal contracts requiring U.S. citizenship and ability to obtain required security clearance.

Lead AI-first payroll tax and compliance product efforts for Workday Payroll US. Define vision and roadmap, assess workflows, prioritize AI-driven compliance features, partner with engineering/ML/design, validate with customers, support issue resolution, and produce clear customer-facing documentation while ensuring solutions are secure, explainable, auditable, and aligned with Workday's AI trust principles.

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.

Lead and execute technology, security, and AI-related audits; assess AI and cloud risks; design and deploy AI-enabled audit tools and automated analytics; train and embed modern audit techniques across the team; ensure audit quality, documentation, and stakeholder advisory.