Quick overview
Job description
About the Role
Lead hands-on engineering for an applied AI and enterprise software team, shaping the technical architecture and product direction alongside the CTO and founders. You will guide a small engineering pod while personally building critical systems and helping turn machine learning into production products.
What You'll Do
Build and lead a pod of three to four engineers, supporting their growth, performance, and hiring while remaining hands-on with key projects.
Own platform architecture and make build-versus-buy and infrastructure decisions.
Establish engineering standards for AI-assisted development, including code review, completion criteria, release cadence, and on-call practices.
Lead technical design and initial implementation of new initiatives.
Evaluate applied ML research and determine what is ready for production systems.
Partner with the CTO on product roadmap, model strategy, and the engineering approach.
What We're Looking For
Typically 5 to 8 years of engineering experience, with exceptional candidates considered from 4 to 5 years.
Experience shipping applied machine learning products, including training and deploying models in production, not only integrating LLM APIs.
Experience owning technical architecture end-to-end, including infrastructure and build-versus-buy decisions.
Track record as a technical lead, pod lead, or manager who has set engineering standards and held engineers accountable.
Recent hands-on software delivery, strong applied ML judgment, and practical experience using AI agents in development.
Experience at an AI-native company and in attracting technical talent; a stable employment history is expected.
Comfort with ambiguity, inherited code, and hands-on work.
Compensation & Benefits
Base salary: $200,000 to $400,000 annually. Visa sponsorship is not available.
Location
On-site in New York City, United States.