About the Role
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.
What You’ll Do

• 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.

What We’re Looking For

• 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.

Compensation & Benefits
Base salary: $200,000 to $400,000 USD annually. Visa sponsorship is not available.
Location
On-site in New York City, United States.

About the Role
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.
What You’ll Do

• 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.

What We’re Looking For

• 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.

Compensation & Benefits
Base salary: $200,000 to $400,000 USD annually. Visa sponsorship is not available.
Location
On-site in New York City, United States.