Founding Engineering Lead

Clera; United States; À distance; USD 200 000 - 400 000; Plein temps

Résumé du poste

Royper Royco LLC seeks a hands-on leader to guide an early-stage SaaS team; you will shape technical architecture and product direction while personally delivering critical builds.

You will build and lead a pod of engineers, own platform decisions, set AI development standards, and drive production ML initiatives. Expect hybrid leadership with remain hands-on initially, expanding as the team scales.

Qualifications

• 5 to 8 years of engineering experience, with 4 to 5 years 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 track 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.

Responsabilités

• 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.

Connaissances

Engineering leadership

ML model deployment

AI architecture

Hiring & team building

Cost management

Hands-on development

Mentorship

Outils

Python

TensorFlow

PyTorch

Cloud infrastructure

Description du poste

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.

Base salary: $200,000 to $400,000 USD annually. Visa sponsorship is not available.

Location

On-site in New York City, United States.