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Luminai

Senior Product Manager, Applied AI

Posted 25 Days Ago
In-Office
New York, NY, USA
170K-250K Annually
Senior level
In-Office
New York, NY, USA
170K-250K Annually
Senior level
Own the Intelligence and Applied AI product area for an AI automation platform. Define benchmarks, evaluation frameworks, and production quality standards; guide model experimentation and determine which capabilities ship. Partner with engineering on platform development, observability, and monitoring, establish operating processes, and enable sales and customer success to communicate AI capabilities accurately.
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About Luminai

Healthcare operations have always depended on people to bridge the gaps that technology couldn't. It relies on complex manual work to carry out critical internal processes, yet most health systems don’t have enough resources to properly automate these tasks, leaving them stuck in outdated, labor-intensive SOPs.
Luminai structures the chaos, automates the manual handoffs, and deploys end-to-end workflows across every system, providing the integrated intelligence layer to improve processes over time. By delegating to autonomous AI systems those mission-critical workflows that previously expended valuable human time, Luminai allows doctors and administrators to do what they do best: Focus on Patients.
We've raised $60M in funding, including our recent Series B led by Peak XV Partners (formerly Sequoia India), with participation from healthcare-focused Define Ventures and continued support from General Catalyst and Y Combinator. We're backed by some of the best investors in Silicon Valley, including Kevin Weil (Chief Product Officer at OpenAI), Arash Ferdowsi (co-founder of Dropbox), Katie Stanton (former VP Global Media, Twitter), and CEOs of companies such as Flexport, Notion, Front, Ramp, and Twitch.

Our team is in-office 4 days a week (Monday - Friday, Wednesday optional WFH) in either San Francisco, California or New York, New York.

About the role

As a Product Manager working on AI systems, you will play a foundational role in directing research, experimentation and rapid improvement of AI systems towards building a capable, reliable AI automation platform. The platform is used by organizations worldwide to deploy and scale executable AI automations in mission critical production environments. You will own the Intelligence and Applied AI product area, which means deciding what the team measures, how fast it can test an idea, and which model capabilities graduate from a promising result into something customers depend on every day. You are expected to have a strong proficiency in fundamentals of product management, a willingness to pick up new concepts as needed and an ability to drive technical projects in ambitious environments.

 

What You'll Do

  • Define which internal AI benchmarks the team optimizes toward and which customer outcomes those benchmarks predict

  • Partner on evaluation frameworks to accelerate the speed and direction of experimentation

  • Decide which model improvements become shipped platform capability and which experiments to stop early

  • Set the bar for accuracy, generalization and failure behavior for automations running in production

  • Collaborate and contribute on the core product development to deliver higher platform capabilities

  • Work with engineering on observability and monitoring systems to safety check model behavior in critical settings

  • Establish how the team operates while working through early-stage questions that don't have obvious answers yet

  • Enable sales and customer success to speak accurately about what the AI does and does not do

 

What We're Looking For

  • Proven track record of shipping AI or ML powered products in challenging projects

  • At least 5 years of product management experience, including 0 to 1 work

  • Fluency in how models are evaluated, where they fail, and what changes between a demo and a production deployment

  • Comfort using evals, benchmarks and model performance data as primary decision inputs

  • Solid fundamentals in system design and technical trade-offs, with the ability to write specifications for technical and non-technical audiences

  • Attention to detail and a first-principles thinking towards real world deployment of intelligent systems

  • Founder and ownership mindset, with experience taking products from ideation through launch and scale

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