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Hyperscience

Enterprise AI platform automating business processes

Lead Technical Product Manager - Platform

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeSofia, Bulgaria

About the Job

Requirements

  • At least 8 years of product management experience at a technology company, ideally working with local and remote engineering teams.
  • A bachelor's degree in engineering, physics, or another technical field, or equivalent industry experience.
  • Strong knowledge of software development principles and architectural best practices.
  • A solid understanding of UI/UX design concepts, user empathy, and requirements gathering to build a compelling product vision.
  • Ability to collaborate across internal teams and with external partners.

Responsibilities

  • Own the end-to-end vision and roadmap for a core product domain, aligning initiatives with company priorities to automate complex workflows.
  • Translate user research and customer pain points into high-quality, extensible features that expand platform capabilities.
  • Direct a cross-functional team of engineers and designers to ship impactful enterprise solutions predictably.
  • Build consensus across internal teams, remote engineers, and external partners from product discovery through launch.
  • Architect scalable capabilities, including APIs, frameworks, and SDKs, that enable clients to build custom solutions.
  • Use suitable tools and services to amplify output while maintaining quality.

Desired Qualifications

  • A proven track record in enterprise software development.
  • Experience designing highly leveraged, scalable platform capabilities.
  • Hands-on familiarity with machine learning paradigms and technologies.

About the Company

Hyperscience

Enterprise AI platform automating business processes

HyperScience offers an enterprise AI platform that automates a range of business processes for B2B customers in sectors like insurance, government, and financial services. The system blends human judgment with machine learning and is trained by humans to handle complex tasks with high accuracy, using industry-ready workflows and customizable modules. It learns from human feedback and maintains administrator visibility, delivering faster throughput and lower costs, with real-world results such as 80% faster claims processing and 96% accuracy. The goal is to help enterprises automate and optimize workflows at scale, saving time and money while reducing manual labor.

Company size
201-500
Company stage
Series E
Total funding
$288.9M
Headquarters
New York City, New York
Founded
2014

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