Senior Machine Learning Engineering Manager – AI Quality and Governance

🕒 July 30

🇺🇸 United States – Remote

💵 $193k - $308k / year

⏰ Full Time

🟠 Senior

👮‍♀️ Software Engineering Manager

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Workiva

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2008

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Workiva is a cloud-based, AI-powered platform that unifies financial reporting, risk and compliance management, and sustainability reporting. It enables teams to connect data across systems, collaborate in real time, automate reporting (including XBRL tagging), and maintain auditability and traceability for regulated disclosures and assurance processes. Workiva serves large enterprises and finance, legal, audit, and sustainability teams to accelerate reporting, improve accuracy, and reduce risk.

📋 Description

• Lead, mentor, and develop a multidisciplinary team of software, ML, and quality engineers • Build a culture of technical excellence, quality ownership, experimentation, and continuous improvement • Establish clear team priorities while balancing platform investments, product needs, and enterprise risk • Define and drive a comprehensive quality strategy for Workiva's AI platform and products, spanning unit, integration, end-to-end, performance, resilience, security, and production testing • Establish measurable quality bars, release-readiness criteria, and automated quality gates for AI and agentic capabilities • Advance testing approaches for nondeterministic systems, including RAG pipelines, agents, prompts, models, tools, and multi-step workflows • Detect regressions, model or data drift, unsafe behavior, and degraded customer experiences before and after release • Lead architecture and delivery of a scalable, self-service evaluation platform for generative AI, RAG, and agentic systems • Build governance into the AI lifecycle through traceability, lineage, versioning, documentation, risk classification, approval workflows, and auditable evidence. • Collaborate with Product, Program Management, UX, UXR, Data Science, Security, Legal, Risk, and engineering leaders to define quality expectations and roadmaps.

🎯 Requirements

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience) • 10+ years in software engineering, ML engineering, quality engineering, or related roles, including 4+ years leading an engineering team • Strong software engineering and systems-design fundamentals, with experience delivering and operating production SaaS or platform capabilities • Demonstrated experience establishing automated quality practices for distributed, cloud-based products • Practical understanding of the generative AI development lifecycle and challenges of evaluating nondeterministic systems • Experience with generative AI concepts: LLMs, RAG, embeddings, vector/hybrid search, agents, tool use, and prompt orchestration • Experience defining measurable quality criteria using data, experimentation, telemetry, and production signals • Experience with cloud-native architectures on AWS, Azure, or GCP.

🏖️ Benefits

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