5-8 years of engineering experience, with flexibility for exceptional candidates with 4-5 years.
Proven experience in shipping applied machine learning products, including model training and deployment.
Ownership of technical architecture, including infrastructure and build-versus-buy decisions.
Demonstrated track record as a technical lead or manager, setting engineering standards.
Recent hands-on software delivery experience with strong applied ML judgment.
Background in AI-native companies and attracting technical talent; stable employment history preferred.
Ability to navigate ambiguity and work with inherited code.
Responsibilities
Build and lead a small engineering pod, focusing on team growth and performance.
Own platform architecture and make strategic build-versus-buy decisions.
Establish engineering standards for AI-assisted development processes.
Lead technical design and initial implementation of new initiatives.
Evaluate applied ML research for production readiness.
Collaborate with the CTO on product roadmap and engineering strategies.
Benefits
Opportunity to shape technical architecture and product direction.
Hands-on leadership role with a focus on team development.
Engagement in cutting-edge applied AI projects.
Collaborative environment with direct access to CTO and founders.
On-site work in New York City, fostering team cohesion.
Full 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
