Lead engineering for an early-stage SaaS company applying machine learning to enterprise software. You will shape technical architecture and product direction while leading a small engineering pod and remaining hands-on with critical builds.
Build and lead a pod of engineers, supporting their growth, performance, and hiring while personally shipping critical work.
Own platform architecture and make build-versus-buy and infrastructure decisions.
Establish engineering standards for AI-assisted development, including review criteria, definition of done, release cadence, and on-call practices.
Lead technical designs and initial implementations for new initiatives.
Assess applied machine learning research and determine what is ready for production systems.
Partner with technical leadership on product roadmap, model strategy, and machine learning direction.
Initially spend most of your time building, with leadership responsibilities growing over time.
Typically 5 to 8 years of engineering experience, with 4 to 5 years considered for exceptional candidates.
Commercial experience training and deploying machine learning models in production, beyond integrating third-party LLM APIs.
Experience at an AI-native company, with technical leadership or ownership and a record of attracting strong engineering talent.
End-to-end ownership of technical architecture, including infrastructure and cost decisions.
Experience setting engineering standards and leading delivery practices for a team.
Recent hands-on experience shipping production software, strong applied ML judgment, and effective use of AI coding agents.
Comfort working through ambiguity, inherited code, and hands-on implementation.
Base salary: $200,000 to $400,000 USD annually. Visa sponsorship is not available.
On-site in New York City, United States.