Technical Product Manager, Platform

BPT Staffing

  • New York, NY
  • 17 days ago
  • $170,000–$190,000 Per Year

Highlights

The TPM will own the creation and continuous improvement of workflows that support new data integrations, data model builds, dashboard configurations, and data integrity flows, working directly alongside engineers and client-facing teams to get high-quality capabilities shipped fast. What matters most is intellectual curiosity around unstructured data, a bias toward doing rather than delegating, and the kind of drive that shows up clearly when you ask them to walk you through a project they owned end to end.

Numbers & Facts

LocationNew York, NY
Salary$170,000–$190,000 Per Year

Description

About the Role

This role sits on the platform engineering team of a growing AI-powered consumer intelligence company, serving major brands across consumer goods, food and beverage, personal care, and adjacent industries. The TPM will own the creation and continuous improvement of workflows that support new data integrations, data model builds, dashboard configurations, and data integrity flows, working directly alongside engineers and client-facing teams to get high-quality capabilities shipped fast.

The ideal candidate has a genuine feel for data, not just familiarity with it. They have worked inside a SaaS or AI product environment, are comfortable being in the weeds with engineers and customers alike, and can move a project from concept to go-live largely on their own initiative. A background that started in engineering is a real plus. What matters most is intellectual curiosity around unstructured data, a bias toward doing rather than delegating, and the kind of drive that shows up clearly when you ask them to walk you through a project they owned end to end.

Key Responsibilities

  1. Design and continuously refine platform workflows that bring new data types and product capabilities to customers quickly and reliably
  2. Lead engineers through releases covering data integrations, data models, dashboard configurations, and data quality pipelines
  3. Carry out hands-on implementation work when new capabilities launch and document the process so the broader team can run it independently
  4. Write small to medium features using AI-assisted coding tools to prototype and accelerate delivery
  5. Partner with customer success and sales teams to resolve technical issues, unblock deals, and sharpen the onboarding experience
  6. Build and maintain clear, reusable resources such as guides and playbooks so operational knowledge scales with the team
  7. Bring structured thinking to ambiguous problems involving unstructured text data, generative AI pipelines, and multi-source data feeds

Required Skills & Experience

  • 2 or more years of experience in a technical product manager, data-adjacent PM, or engineer-to-product role
  • Bachelor's degree in computer science, engineering, or a related technical field
  • Demonstrable comfort working with data: querying, scripting, understanding pipelines, and making sense of unstructured text data
  • Experience at a SaaS or AI company where product decisions were closely tied to data architecture or processing
  • Ability to write a clear PRD, translate user requirements into engineering tasks, and hold your own in a technical design session
  • Startup readiness: can point to a project they drove from concept to production with real ownership, not just a slice of influence
  • Must be authorized to work in the US without visa sponsorship now or in the future

Preferred Skills

  • Exposure to generative AI tooling, agentic workflows, or large-scale text processing in a product or quasi-engineering context
  • Experience with APIs, ETL or data pipeline concepts, and database querying in a product context
  • Background as a knowledge engineer, data PM, or similar role where the core job was deciding what data to use, how to transform it, and how to surface it
  • Comfort prototyping with AI coding assistants such as Claude to move fast without waiting on engineering
  • Prior work with enterprise clients during onboarding or implementation, especially in a hands-on technical capacity

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