Principal Product Manager - AI Data Quality

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation. Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better. And it means we prioritize a diverse F5 community where each individual can thrive.The Mission We are building an AI-native enterprise, and high-fidelity data is the substrate. We are looking for a technically fluent Product Manager to architect and scale an AI-Ready Data Quality Platform built on Databricks and Unity Catalog. This is not a traditional MDM or stewardship role. You will define and ship the platform capabilities that make our AI Data Fabric trustworthy, observable, and production-grade — from real-time anomaly detection to CI/CD-native schema enforcement to automated data contract validation. If you think of data quality as code, treat governance as infrastructure, and believe AI systems are only as good as the data feeding them — this role is for you. What You’ll Own Build the AI-Ready Data Quality Platform Define and ship native data quality capabilities inside Databricks Lakehouse Productize policies and controls within Unity Catalog (lineage, access, schema enforcement) Embed data contracts and validation logic directly into pipelines Partner with data engineering to integrate dbt-based transformation layers into quality frameworks Drive metadata, lineage, and semantic standardization as first-class platform features Operationalize Data Quality in the AI Data Fabric Design real-time anomaly detection systems (statistical + ML-driven) Build upstream schema validation into CI/CD workflows (shift-left quality) Define SLOs/SLAs for data products Enable automated drift detection for training and inference datasets Implement observability across streaming and batch architectures You will treat data quality like SRE treats uptime. Drive Data Ownership as a Product Discipline Establish a data product ownership model across service teams Define what “production-grade data” means for AI use cases Build self-service tooling for teams to monitor and certify their data Incentivize measurable quality accountability at the domain level This role transforms culture by building the platform that enforces it. AI + Governance Convergence Define how governed datasets become AI-ready assets Enable traceability from raw source curated feature sets model inputs Align catalog metadata with AI feature stores and inference pipelines Partner with ML teams to support model reproducibility and dataset versioning What You Bring 5+ years in Product Management for Data Platforms, Analytics, or AI Infrastructure Deep working knowledge of: Databricks Lakehouse architecture Unity Catalog governance constructs dbt transformation workflows CI/CD patterns for data pipelines Data observability and monitoring patterns Strong SQL fluency and comfort reading Python/Scala data pipeline code Experience defining data contracts and schema evolution strategies Understanding of streaming frameworks (Kafka, Spark Structured Streaming, etc.) Experience supporting AI/ML workloads in production environments Bonus: Experience with modern data observability platforms (Monte Carlo, Bigeye, etc.) Familiarity with feature stores and model lifecycle tooling Knowledge of domain-oriented data mesh architectures How We Measure Success % of AI datasets certified as “production-grade” Reduction in downstream model failures due to data issues Automated anomaly detection coverage across critical pipelines Adoption of data ownership model across service domains CI/CD-integrated data validation coverage Why This Role Matters AI systems amplify whatever data they are fed. This role ensures: We trust our data. Our models are reproducible. Governance is automated. Quality is engineered, not inspected. You won’t be managing spreadsheets of bad records. You will be building the infrastructure that makes AI reliable at scale. #LI-JB1The Job Description is intended to be a general representation of the responsibilities and requirements of the job. However, the description may not be all-inclusive, and responsibilities and requirements are subject to change.The annual base pay for this position is: $156,800.00 - $235,200.00F5 maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, geographic locations, and market conditions, as well as to reflect F5’s differing products, industries, and lines of business. The pay range referenced is as of the time of the job posting and is subject to change.You may also be offered incentive compensation, bonus, restricted stock units, and benefits. More details about F5’s benefits can be found at the following link: . F5 reserves the right to change or terminate any benefit plan without notice. Please note that F5 only contacts candidates through F5 email address (ending with @f5.com) or auto email notification from Workday (ending with f5.com View email address on click.appcast.io).Equal Employment OpportunityIt is the policy of F5 to provide equal employment opportunities to all employees and employment applicants without regard to unlawful considerations of race, religion, color, national origin, sex, sexual orientation, gender identity or expression, age, sensory, physical, or mental disability, marital status, veteran or military status, genetic information, or any other classification protected by applicable local, state, or federal laws. This policy applies to all aspects of employment, including, but not limited to, hiring, job assignment, compensation, promotion, benefits, training, discipline, and termination. F5 offers a variety of reasonable accommodations for candidates. Requesting an accommodation is completely voluntary. F5 will assess the need for accommodations in the application process separately from those that may be needed to perform the job. Request by contacting View email address on click.appcast.io: SeattleType: Full time