Senior Staff Machine Learning Engineer - US
About The Position
Workiva is seeking a Senior Staff Machine Learning Engineer to define how AI is architected, deployed, and trusted across its platform at enterprise scale. The role focuses on accuracy, auditability, security, and reliability for mission-critical workflows used by large, regulated organizations. The engineer will own the architecture of Workiva’s AI platform and core AI services; shape the integration of machine learning, Generative AI, and agentic systems across products; and lead the transition to production-grade, enterprise-ready systems. The role establishes standards for model serving, retrieval, evaluation, governance, and platform reliability. This position also leads enterprise agentic system design, including orchestration, workflow execution, memory, and multi-agent coordination; evolves Retrieval-Augmented Generation capabilities; and establishes evaluation and quality frameworks for Generative AI. It provides technical direction across teams and platform domains, mentors Staff and Senior Engineers, and partners with Product, Security, Infrastructure, and Architecture leaders. The role leads secure AI platform design and best practices for AI safety, model governance, and customer data protection. It ensures enterprise expectations for availability, resiliency, observability, and operational support are met, with fault tolerance and operational excellence in regulated, security-conscious environments. Workiva supports employees working from an office or remotely from any location within their country of employment. Travel is less than 10%, and reliable internet access is required for remote working opportunities.
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.
Nice To Haves
- 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.
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 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.
- Complete comprehensive security and privacy training tailored to the role and adhere to company policies and regulatory standards.
Benefits
- A discretionary bonus typically paid annually.
- Restricted Stock Units granted at time of hire.
- 401(k) match and comprehensive employee benefits package.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
