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Saunders Scott Linkedin · Posted 7d ago

Applied AI Engineer

New York City, New York, United States

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Indexed description

Applied AI Engineer


Architect and build production-grade AI applications from zero to one


You will own end-to-end development of production AI systems serving real customers from day one.


  • Competitive base salary and benefits
  • Meaningful upside participation in the value you create
  • Direct access to 50+ portfolio companies and their operations
  • Flat structure with direct access to leadership
  • Your code reaches thousands of users from day one


Technical Excellence


Strong engineering fundamentals with experience building production AI systems.

Comfortable across the stack, e.g. infrastructure (K8s, cloud platforms), backend (Python, FastAPI), and frontend (React, TypeScript).


  • Architect and build production-grade AI applications from zero to one
  • Design systems that handle enterprise-scale data and millions of users from day one
  • Implement everything from model serving infrastructure to polished user interfaces
  • Make critical technical decisions balancing innovation with reliability
  • Ship with velocity: build like a start-up, scale like an enterprise
  • Able to pick up new languages and technologies quickly as builds vary across portfolio companies.
  • Hands-on experience with modern AI/ML frameworks and deployment patterns, including generative AI.
  • Track record of shipping products that scale to thousands of users.
  • Navigate the complexity of implementing AI in messy, regulated, legacy-filled enterprise environments
  • Build solutions that work with imperfect data, demanding SLAs, and complex stakeholder requirements
  • Transform cutting-edge research into revenue-generating products, not demos
  • Tackle technically challenging problems across fintech, enterprise SaaS, B2B services and more
  • Lead product development across multiple portfolio companies and industries
  • Hone your skills across different verticals in 9-18 month sprints
  • Build institutional knowledge about what makes AI products succeed or fail
  • Own the entire AI product lifecycle from ideation to production
  • Demonstrated ability to ship fast without sacrificing quality
  • Experience in high-growth startups or equally fast-paced environments
  • Strong opinions, loosely held: able to make decisions with incomplete information

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