Senior Staff Machine Learning Engineer - US

Workiva is building a next-generation AI platform for mission-critical workflows used by some of the world’s largest and most regulated organizations. They are seeking a Senior Staff Machine Learning Engineer to define how AI is architected, deployed, and trusted across their platform at enterprise scale, ensuring accuracy, auditability, security, and reliability.

Responsibilities:

• Own the architecture of Workiva’s AI platform and core AI services
• Shape how machine learning, Generative AI, and agentic systems are integrated across products
• Lead the move from early adoption to production-grade, enterprise-ready systems
• Define standards for model serving, retrieval, evaluation, governance, and platform reliability
• Lead the design of enterprise agentic systems, including orchestration, workflow execution, memory, and multi-agent coordination
• Design and evolve Retrieval-Augmented Generation capabilities for enterprise content and knowledge workflows
• Establish evaluation methods and quality frameworks for Generative AI applications
• Assess emerging AI technologies and guide adoption strategy for Workiva’s platform
• Influence technical direction across teams, products, and platform domains
• Mentor Staff and Senior Engineers and help raise the technical bar across the organization
• Partner closely with Product, Security, Infrastructure, and Architecture leaders
• Align teams around a shared vision for scalable, secure AI at Workiva
• Lead secure AI platform design, including authorization, runtime isolation, governance, auditability, and compliance
• Establish best practices for AI safety, model governance, and customer data protection
• Ensure AI systems meet enterprise expectations for availability, resiliency, observability, and operational support
• Design for fault tolerance and operational excellence in regulated, security-conscious environments

Requirements:

• Bachelor's degree in Computer Science, Engineering, or equivalent experience
• 10+ years of software engineering experience, including large-scale SaaS platforms
• 5+ years designing, deploying, and operating production ML, AI, or data-intensive systems
• Experience designing and operating enterprise AI platforms, including model serving, evaluation, observability, and governance
• Deep expertise in RAG, agentic systems, and large-scale knowledge systems
• Strong understanding of foundation model ecosystems, including inference, routing, prompting, and provider tradeoffs
• Experience with AI evaluation, secure AI systems, and regulated enterprise environments
• Proven track record leading architecture across multiple teams or platform domains
• Strong distributed systems, cloud-native, API, reliability, and operational excellence experience
• Expert-level Python proficiency and proficiency in at least one production language such as Java, Go, Scala, or C++
• Proven record mentoring senior engineers and technical leaders