Lead, mentor, and develop a team of machine learning and software engineers focused on building the intelligent backbone of the Workiva AI platform.
Provide hands-on coaching, performance feedback, and growth opportunities for engineers at varying experience levels.
Foster a collaborative, inclusive, and high-ownership team culture grounded in trust, accountability, and continuous improvement.
Collaborate closely with Product, Program Management, UX and UXR to lead and develop engineers in owning development, maintaining AI & ML infrastructure, and seamlessly integrating Generative AI and Machine Learning features into products.
Work with internal engineering teams and developers to understand integration needs and remove friction.
Communicate complex technical issues to both technical and non-technical audiences effectively.
Oversee the design, implementation, and maintenance of foundational AI/ML services.
Guide architectural decisions to ensure platform scalability, reliability, and alignment with Workiva’s long-term technical vision.
Ensure engineering best practices around security, testing, operational excellence, and documentation.
Drive improvements in latency, service availability, developer experience, and integration usability across internal and external interfaces.
Maintain high service availability and performance across various ML services.
Champion observability, incident response readiness, operational improvements and managing team’s support rotations.
Reduce complexity through simplification, automation, and thoughtful system design.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience
7+ years of total experience in software engineering and/or Machine Learning, with at least 2 years of dedicated experience as an Engineering Manager
Strong understanding of ML development cycles and toolsets
Experience with core concepts of Generative AI such as RAG, Agentic frameworks, etc.
Solid experience in delivering SaaS products, specifically hosted in AWS, Azure, or GCP
Proven ability to manage senior individual contributors, resolve technical conflicts, and build a culture of psychological safety and high performance
Master’s degree in Computer Science, Engineering, Data Science or equivalent combination of education and experience. (Preferred)
Experience leading teams of up to 5 people, preferably with diverse skill sets and specializations (Preferred)
Excellent problem-solving skills, with the ability to address customer needs and improve product experiences (Preferred)
Background in cloud-native architectures (GCP, AWS, or similar). (Preferred)
Familiarity with Kubernetes, microservices, and modern DevOps practices (Preferred)

Benefits

A discretionary bonus typically paid annually
Restricted Stock Units granted at time of hire
401(k) match and comprehensive employee benefits package

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningGenerative AISaaSAWSAzureGCPKubernetesmicroservicesDevOpsAI/ML infrastructure

Soft Skills

leadershipmentoringcollaborationcommunicationproblem-solvingpsychological safetyaccountabilitycontinuous improvementteam cultureperformance feedback

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringBachelor’s degree in Data ScienceMaster’s degree in Computer ScienceMaster’s degree in EngineeringMaster’s degree in Data Science