Senior Product Manager

We are looking for a Senior Product Manager to own the platform where humans and AI work together on live financial data and the review and feedback layer that supplements our AI extraction systems. Every correction, override, and judgment call a human analyst makes in this product is a signal. Your job is to design the experience so that the signal gets captured cleanly and routed back into the systems that need it: better context for the model at the point of decision, structured feedback loops, and inputs that improve the accuracy of our data. As coverage expands into new regions, document types, and event types, this layer is what keeps quality improving across this expanding perimeter.

You will work closely with engineering, operations, and product leadership to design review workflows that are fast for the analyst and help tune AI, and to build the instrumentation that turns human review into a compounding asset. This is a high-ownership role for someone deeply technical, highly execution-oriented, and excited about building the human-AI interface for a real-world AI system at scale.

Responsibilities:

• Own the roadmap for the review and feedback experience, covering how analysts see model context, make corrections, and resolve disagreements between AI output and ground truth.
• Design context management into the workflow, surfacing the right source documents, prior decisions, and model reasoning at the moment an analyst needs to judge or correct an output, so review speed doesn't trade off against review quality.
• Build the feedback and tuning loop end to end: capture structured signal from every human correction, route it to the AI/ML team in a form they can act on, and close the loop by measuring whether it changed downstream accuracy.
• Partner with engineering and AI/ML to define what needs to be reviewed, what the ideal review experience is, and how it endures with future AI model updates.
• Instrument the full workflow from document to reviewed datapoint, with a single metric the team can rally around for review speed and error rate.
• Collaborate cross-functionally across Product, Engineering, and Operations to align priorities, execute quickly, and deliver measurable business impact.
• Stay current on advancements in AI/LLMs and apply emerging capabilities, particularly around human-in-the-loop tuning and RLHF-style feedback, thoughtfully into platform strategy and execution.

Requirements:

• We're looking for a highly technical product manager with 3+ years of experience building AI/ML product features or workflow/tooling products and 8+ years of PM experience at Series B or later companies.
• Have experience owning complex platform or workflow products end-to-end, ideally ones where humans review or correct AI/ML output.
• Have worked closely with AI/ML systems, LLM workflows, or human-in-the-loop annotation and review tooling.
• Understand the mechanics of feedback loops: how to capture a human correction as a structured signal and how that signal should reach a model or tuning pipeline.
• Can design for two audiences at once: the analyst doing the review and the AI/ML system consuming what the review produces without over-indexing on either.
• Can comfortably work with highly technical teams and participate in architecture and system design discussions.
• Have strong product judgment and can balance review speed, data quality, and operational complexity.
• Are highly analytical and comfortable balancing the use of data and domain-specific intuition to drive prioritization and decision-making.
• Have experience designing experimentation frameworks, benchmark evaluations, or feedback loop systems.
• Possess strong written and verbal communication skills and can simplify complex technical concepts.
• Thrive in fast-paced, ambiguous environments with high ownership and autonomy.

Preferred Qualifications

• Have shipped, as an IC, at least 1 AI-native product or agentic workflow or hybrid ML/LLM system into production at a 1K+ DAU or transaction per day scale.
• Shipped at least 1 human-in-the-loop review, annotation, or QA tooling product feature to at least 1K+ DAU.
• Familiarity with SQL, experimentation frameworks, and product analytics tools.
• Experience scaling review or QA workflows across multiple workflows, geographies, or datasets.
• Background in B2B SaaS, AI infrastructure, or FinTech products.