Senior ML Quality & Governance Engineering Manager

Sustain.Life; United States; Remote; USD 193,000 - 308,000; Full time

Benefits offered by this job

Restricted Stock Units

401(k) match

Discretionary bonus

Employee benefits package

Job summary

Workiva is hiring a Sr Machine Learning Engineering Manager - AI Quality and Governance to lead a multidisciplinary team focused on end-to-end quality and governance for enterprise-grade AI products. You will drive quality strategy across AI platform services, RAG/agentic systems, and governance capabilities while partnering with Security, Legal, and Risk teams.

The role requires 10+ years in software/ML engineering with 4+ years leading teams, strong expertise in cloud-native architectures, and

Qualifications

• 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
• Proven ability to lead senior individual contributors, navigate technical disagreements, and build high-performance cultures
• Strong communication and cross-functional leadership skills

Responsibilities

• 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
• Recruit engineers with complementary expertise across software quality, ML evaluation, platform engineering, and governance automation
• Define and drive a comprehensive quality strategy for 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
• Enable teams to create, manage, version, and reuse evaluation datasets, golden test sets, task-specific metrics, graders, and benchmarks
• Support deterministic checks, statistical metrics, model-based graders, human evaluation, adversarial testing, and domain-expert review
• Build capabilities for offline evaluation, pre-release regression testing, online experimentation, production sampling, and continuous evaluation
• Ensure evaluation results are reproducible, explainable, actionable, and integrated into developer workflows, CI/CD pipelines, and operational dashboards
• Translate Workiva's Responsible AI principles into practical engineering controls and platform capabilities
• Build governance into the AI lifecycle through traceability, lineage, versioning, documentation, risk classification, approval workflows, and auditable evidence
• Partner with Security, Legal, Privacy, Compliance, and Risk teams to define controls that support enterprise and regulated use cases
• Enable inventories and traceability across models, prompts, datasets, evaluations, tools, knowledge sources, and deployed AI features
• Collaborate with Product, Program Management, UX, UXR, Data Science, Security, Legal, Risk, and engineering leaders to define quality expectations and roadmaps
• Influence engineering teams across Workiva to adopt shared evaluation standards, testing practices, observability, and release controls
• Communicate complex technical tradeoffs, quality signals, and risk findings clearly to technical and non-technical audiences
• Ensure the evaluation and governance platform is secure, scalable, reliable, observable, and cost-effective
• Define service-level objectives and meaningful operational and quality metrics
• Champion production readiness, incident response, root-cause analysis, and continuous operational improvement

Skills

Software engineering fundamentals

ML engineering

Quality engineering

Leadership

Communication

Cloud architectures

Cross-functional collaboration

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related field

Tools

Kubernetes

CI/CD

Infrastructure as Code

Job description

Workiva is hiring a Sr Machine Learning Engineering Manager - AI Quality and Governance to lead a multidisciplinary team focused on end-to-end quality and governance for enterprise-grade AI products. You will drive quality strategy across AI platform services, RAG/agentic systems, and governance capabilities while partnering with Security, Legal, and Risk teams.

The role requires 10+ years in software/ML engineering with 4+ years leading teams, strong expertise in cloud-native architectures, and