Sr. Product Manager
$100,000–$180,000 year
RemoteUnited States
Job Summary
Own intake and prioritization for AI app, automation, and agent requests across Finance, Ops, Data Services, and CX. Define the operating model that transforms business-built proof of concepts into hardened, secure production systems on a shared GCP platform. Establish governance standards for access controls, secrets management, and monitoring while enforcing responsible AI frameworks like NIST AI RMF and the EU AI Act. Partner with business unit leaders to drive buy-vs-build decisions, manage stakeholder expectations, and ensure adoption through training and documentation. Define eval sets and acceptance criteria for non-deterministic models, monitor outputs in production, and lead incident response when quality thresholds are missed. Track metrics including adoption rates, time-to-production, and inference costs to forecast economics and report value to the C-suite.
Required Qualifications
- 7+ years in product management, technical program management, or a closely related IT/platform role
- Demonstrated ownership of intake and prioritization for a portfolio of competing internal requests
- Working fluency in software delivery and platform concepts: CI/CD, environments, auth/identity, secrets management, monitoring, and cloud (GCP preferred; AWS/Azure acceptable)
- Practical understanding of AI/LLM application patterns (assistants, agents, retrieval, automations) and the governance questions they raise
- Familiarity with the model lifecycle and MLOps fundamentals, including eval sets, prompt and model versioning, monitoring for drift and regression, and the difference between shipping a deterministic feature and shipping a probabilistic one
- Strong grasp of security and data-governance fundamentals, including access controls, data classification, least privilege, and audit
- Working knowledge of responsible-AI frameworks and emerging regulation (NIST AI RMF, EU AI Act, model-risk management), and the practical questions they raise about bias, explainability, and human oversight
- Excellent written and verbal communication; able to align engineers, business owners, and executives
Desired Qualifications
- Experience standing up or governing an internal developer/AI platform shared across business units
- Experience with enterprise-level software integrations, driven by APIs across systems such as NetSuite, Salesforce (and Agentforce), Slack, and SQL data platforms
- Background in regulated or data-sensitive environments (finance, insurance, healthcare data schemas such as Epic)
- Experience leading buy-vs-build evaluations of vendor AI tooling
- Experience running AI/SaaS vendor evaluations end-to-end with Security, Procurement, and Legal, including security reviews, SOC 2 / ISO 27001, DPAs, and model-use terms
- FinOps or cloud-cost-management experience, ideally with exposure to AI inference economics
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