Sr. Product Manager

Position Overview
We are seeking an experienced and driven Product Manager, Business Process Modernization & Intelligent Automation to lead the strategy, design, and execution of next-generation business process and workflow systems. This role is central to modernizing how our organization operates internally — replacing manual, rules-static processes with intelligent, adaptive systems that scale with the business.
You'll own the roadmap for transforming core operational workflows, with two flagship initiatives: (1) embedding AI-driven, human-in-the-loop validation for exception handling on cases the system can't yet resolve on its own, and (2) building a real-time, self-learning rules engine that governs data ingestion and streaming as it happens — not after the fact.
This role reports directly to SVP Shared Services and will work cross-functionally with engineering, data science, operations, and staff who run these processes daily. The ideal candidate has a strong background in enterprise/internal-tools product management, process automation, and applied AI/ML products, and is comfortable operating at the intersection of business process design and real-time data systems.
Key Responsibilities
Product Strategy & Execution

Own and evolve the roadmap for business process modernization, workflow automation, and system optimization initiatives.
Identify and prioritize opportunities to eliminate manual bottlenecks and increase staff and system capacity/throughput.
Lead end-to-end product lifecycle — from process discovery and current-state mapping through delivery and iteration.
Lead AI-driven initiatives that introduce human-in-the-loop validation for unknown or unresolved exceptions, ensuring the system escalates appropriately while continuously learning from resolved cases.

Intelligent Data Ingestion & Streaming

Define and drive the product vision for a rules-based engine that governs data ingestion and streaming in-flight — capable of learning and adapting in real time as new patterns and exceptions emerge.
Partner with engineering and data teams to design decisioning logic that balances automation with configurable business rules and guardrails.
Establish feedback loops so the engine's rules evolve based on outcomes, staff overrides, and changing business conditions.

Cross-functional Collaboration

Partner closely with engineers, data scientists, and business operations leads to design and launch process and system improvements.
Translate operational pain points and staff feedback into clear product and technical requirements.
Align stakeholders across business operations, data, and engineering to drive unified delivery.

Process & Workflow Optimization

Use quantitative and qualitative data to understand where current workflows break down and where automation/AI can create the most leverage.
Define and track KPIs around exception rates, resolution time, automation coverage, and staff productivity.
Champion structured experimentation to validate process changes before full rollout.

Human-in-the-Loop & Change Management

Design workflows that keep staff appropriately "in the loop" — reviewing, validating, and correcting AI decisions on ambiguous or unknown cases.
Work with operations teams to ensure new tools enhance staff capability rather than create friction or distrust in automated systems.

Qualifications

5+ years of experience in product management, ideally with a focus on internal/enterprise tools, business process automation, or workflow systems.
Proven experience leading initiatives involving AI/ML products, particularly those with human-in-the-loop or exception-handling components.
Strong analytical mindset with experience using data to evaluate process performance (SQL or similar required).
Familiarity with real-time dastemta sys, streaming architectures, or rules engines (e.g., Kafka, Flink, or comparable) — hands-on engineering experience not required, but fluency in the concepts is.