Job Description:
• 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