Senior Principal, Product Management

Role Overview

• Define and socialize the multi-year MLOps platform roadmap, spanning model training, evaluation, deployment, monitoring, and retirement across global regions
• Architect product solutions for multi-region model inference with data residency constraints — ensuring our models operate compliantly across jurisdictions without sacrificing performance
• Drive model observability and drift detection capabilities from concept to adoption, in partnership with Data Science and Engineering
• Own the vendor and tooling strategy across the MLOps stack evaluating build vs. buy tradeoffs with a clear lens on total cost of ownership and compliance posture
• Publish the Agent Framework Reference Architecture defining how autonomous and semi-autonomous agents are designed, tested, and deployed within a regulated FinServ environment
• Lead product strategy for agentic workflow reliability, including human-in-the-loop design patterns, tool-use governance, and failure mode handling
• Champion model governance as a product capability not a compliance checkbox by embedding risk controls directly into the platform so teams can move fast within guardrails
• Drive adoption of the Model Governance Framework with Model Risk Management (MRM) teams, ensuring our AI systems meet regulatory expectations across all deployment regions
• Define meaningful KPIs and observability standards that allow risk and compliance teams to assess model health without becoming a bottleneck to innovation
• Develop and maintain a model risk taxonomy that scales across foundation models, fine-tuned models, and agentic systems
• Partner with Applied ML, Engineering, Product, Finance, and Procurement to ensure alignment on strategy, performance, and cost.
• Represent the MLOps and Agent Frameworks product domain to senior leadership, translating complex technical tradeoffs into strategic narratives that drive decision-making

Requirements

• 8+ years of product management experience, with at least 3 years focused on ML infrastructure, MLOps platforms, or AI/ML product strategy
• Experience partnering directly with Data Science/Applied ML and Engineering teams.
• Demonstrated experience shipping ML platform or AI infrastructure products in a regulated industry — financial services, healthcare, or similarly complex environments strongly preferred
• Hands-on experience/ strong familiarity with MLOps tooling (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, Databricks) and the ability to evaluate them critically as a product strategist
• Working knowledge of LLM orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen, CrewAI) and the architectural tradeoffs they represent
• Demonstrated experience managing build vs. buy decisions or large-scale vendor evaluations.
• Excellent communication skills and ability to work across product, engineering, and commercial teams.
• Willingness to support deal cycles with competitive insights and analytics expertise.

Benefits

• Healthcare insurance
• We provide medical, dental, and vision insurance, and a flexible spending account that allows you to set aside pre-tax dollars to pay for eligible out-of-pocket expenses.
• Personal time off
• A healthy work-life balance is critical to your success at the office. Smarsh offers a “take-what-you-need” time off policy as well as flexible work arrangements
• 401K Match
• Smarsh provides a 4% 401K match for which employees are fully vested on day one.
• Sabbatical – The Smarsh sabbatical program provides a time to recharge, to study or simply a time to do something you are passionate about away from the workplace. Employees are eligible after six years of service.
• Recognition
• We’re big on kudos for a job well done. Our employee-recognition program enables co-workers to nominate their peers who best embody our core values for recognition