Sr. Principal, Product Management

Who are we?

Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc.

5000 list of fastest-growing American companies since 2008.

Smarsh is the world’s leading provider of intelligence on sensitive communications for regulated industries. Global banks, insurers, and enterprises rely on Smarsh to detect risk, reduce noise, uncover insights, and apply compliant AI  AI/ML platform integrates audio analytics, speech‑to‑text, OCR, translation, classification, and language identification to power supervision, surveillance, investigations, and next‑generation GenAI‑enabled workflows.

The AI Analytics capabilities and AI/ML models serve as core platform services used by every Smarsh product. Ensuring that the MLOps and Agentic infrastructure is robust and scalable while aligned with technology landscape is of strategic importance to the company.

We are seeking a product leader to own MLOps and Agentic strategy for Smarsh’s Analytics Platform. Models are proliferating faster than the infrastructure to govern them, and agentic workflows are moving from proof‑of‑concept to production with real money, real customers, and real regulatory scrutiny on the line. This is not a role for someone who thinks about MLOps and agent frameworks separately.

We need a product leader who sees them as two sides of the same coin: the platform that governs how models are built, deployed, and monitored, and the orchestration layer that determines how those models act autonomously on behalf of our business and customers.

As an Individual Contributor Director, you will operate with the seniority and strategic authority of a Director while remaining deeply embedded in the work of shaping roadmaps, influencing architecture, and driving adoption across engineering, risk, compliance, and business stakeholders. You will report directly to the VP of Product and own one of the most consequential product domains in our AI strategy.

• MLOps Platform Strategy
• 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 trade‑offs with a clear lens on total cost of ownership and compliance posture

• Agent Frameworks & Orchestration
• Publish the Agent Framework Reference Architecture efining how autonomous and semi‑autonomous agents are designed, tested, and deployed within a regulated Fin Serv environment
• Lead product strategy for agentic workflow reliability, including human‑in‑the‑loop design patterns, tool‑use governance, and failure mode handling
• Define and document the Bring Your Own Model establishing how the organization governs the introduction of external models and custom prompts while maintaining auditability and control
• Translate emerging agent framework patterns (e.g., multi‑agent orchestration, RAG pipelines, memory and context management) into concrete product requirements and phased delivery plans

• Model Governance & Risk
• 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…