As a Sr. Model Governance Engineer, you will help to ensure that AI/ML models are developed, deployed, and monitored in a controlled, transparent, and compliant manner. This role partners closely with engineering, data science, risk, compliance, and product teams to support strong model governance practices and keep models auditready.
What You Will Do (Essential Responsibilities):
Maintain the enterprise model inventory, including model owners, purpose, risk rating, and deployment status
Apply model risk ratings and confirm required governance steps are completed
Coordinate model release approvals, evidence collection, and sign off processes
Manage versioning, archiving, and traceability for models and related documentation
Ensure models have complete and standardized documentation, such as Model Cards
Document model intent, assumptions, limitations, and known risks
Capture explainability considerations and any human in the loop processes used
Maintain data lineage and dataset information for training, validation, and monitoring
Ensure required validation evidence is available, including performance and testing results
Support stress testing or review activities for higher risk models
Help set up and support ongoing model monitoring activities
Trigger governance reviews when model, data, or scope changes occur
Partner with engineering, data science, risk, compliance, and governance teams
Produce clear and consistent governance documentation for both technical and non-technical audiences
Support the preparation and review of datasets used for model testing and validation
Support or participate in governance reviews, validations, or review meetings
What You Will Need (Required Knowledge, Skills & Abilities):
Bachelor’s degree, or higher, in a technical or quantitative field (Computer Science, Engineering, Statistics, Mathematics, or similar)
Knowledge, skills and abilities typically gained through 5+ years of experience in model governance, model validation, analytics, or related engineering roles
Experience managing model documentation, approvals, controls, or lifecycle tracking
Understanding of AI/ML models and how they are developed, tested, and used
Familiarity with model validation concepts and benchmarking approaches
Working knowledge of programming languages such as Java and Python
Familiarity with common data formats such as CSV and JSON
Experience writing or reviewing SQL and querying databases, including working with datasets for testing or validation
Understanding of application development concepts and software development lifecycles
Familiarity with SDKs, APIs, and integration patterns used in production systems
Experience working with or supporting systems deployed on cloud platforms (e.g., AWS, Azure, or GCP)
Ability to review technical implementations to understand how models are built, deployed, and monitored
Experience using documentation or tracking tools to support governance, review, or audit activities
Awareness of data privacy and security considerations when working with model data and datasets
What Would be Nice (Preferred Skills & Experience):
Experience supporting models used in fraud, risk, or decisioning systems is a plus
Knowledge of regulatory or governance expectations related to model risk is a plus
Who You Are (Soft Skills & Attributes):
Clear communicator, who can explain complex technical topics simply
Confident presenter, able to share information to various types and levels of stakeholders
Able to work across multiple teams and stakeholders
Detail‑oriented with a strong focus on documentation and accuracy, paired with the ability to identify gaps or issues
Comfortable working in risk‑aware and regulated environments
Organized and methodical in how you manage work and information
Proactive and comfortable taking ownership of governance tasks
What We Offer You (Why Join Us?):
Flexible hours with the possibility to work full remote (in the US) or from our San Diego office.
You'll be able to share feedback to shape and drive innovation using the latest technologies.
Opportunities to contribute to a highly diverse, inclusive an Agile native ecosystem.
Training and development opportunities in a fast-growing industry.
Highly competitive salary + bonus, perks and benefits.
A fun and inclusive work environment where teams succeed together.
