Hybrid Technical Product Manager, Document Intelligence

Chronograph; United States; Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Flexible work arrangements

Competitive salary

401k

Unlimited vacation

Generous health benefits

Parental leave

Job summary

Chronograph is a leading data analytics platform for private capital markets. We are seeking a technically fluent, systems-minded product leader to own the data extraction layer and guide its evolution as AI enables agentic workflows.

You will partner with engineering, applied AI, and client teams to define extraction strategies across OCR, layout-aware models, and vision-language/LLM approaches, design end-to-end pipelines, and ensure accuracy at scale.

Qualifications

• Experience owning end-to-end extraction tools from concept to launch.
• Proven track record building eval-driven quality at scale.
• Ability to spec extraction logic for engineers and cross-functional teams.
• Experience with AI-native workflows and agentic tools.

Responsibilities

• Own the data extraction roadmap and ingestion architecture.
• Define the extraction techniques mix for document types.
• Design end-to-end extraction pipeline including human review.
• Collaborate with ML/AI teams and client-facing functions.
• Set accuracy targets and evaluation frameworks.
• Translate roadmap into concrete product plans and releases.

Skills

VLM-native extraction

LLM-based extraction

OCR

Document intelligence

Product leadership

Stakeholder communication

Tools

Layout-aware models

Vision-language models

Data pipelines

Job description

Chronograph is a leading data analytics platform for private capital markets. We are seeking a technically fluent, systems-minded product leader to own the data extraction layer and guide its evolution as AI enables agentic workflows.

You will partner with engineering, applied AI, and client teams to define extraction strategies across OCR, layout-aware models, and vision-language/LLM approaches, design end-to-end pipelines, and ensure accuracy at scale.