Engineering Lead, AI Infra & Production (Hands‑On)

Datalab; New York (NY); On-site; USD 300,000 - 350,000; Full time

Job summary

Datalab in New York City is seeking an engineering lead to guide our small team while staying hands-on in code. You’ll set technical direction for our OCR, extraction, and document-understanding systems, and you’ll influence interfaces, tools, and infrastructure driving inference speed.

This player-coach role manages three engineers, owns engineering delivery and quality, and spends substantial time coding architecture, infrastructure, and reviews.

Qualifications

• 7+ years engineering experience with 2+ years leading engineers
• Production systems that handle high-volume traffic
• Strong backend or fullstack depth with architectural judgment
• Experience building with LLMs and agentic workflows
• Experience in early-stage startup environments

Responsibilities

• Manage and grow a team of three engineers, including 1:1s, prioritization, feedback and hiring as we scale
• Own engineering delivery, quality, and technical standards across code, testing, infrastructure and deployment
• Stay hands-on ~40-50% of your time, contributing architecture, infrastructure, and code reviews across our repos, API, and internal tooling
• Contribute to the research-to-production interface: set standards for turning research prototypes into reliable systems
• Partner with the research team to align on what’s ready to productionize and how
• Help set engineering priorities and the roadmap alongside the founder

Skills

Team leadership

Backend & fullstack

LLMs & agentic workflows

Production systems

Startup experience

Job description

Datalab in New York City is seeking an engineering lead to guide our small team while staying hands-on in code. You’ll set technical direction for our OCR, extraction, and document-understanding systems, and you’ll influence interfaces, tools, and infrastructure driving inference speed.

This player-coach role manages three engineers, owns engineering delivery and quality, and spends substantial time coding architecture, infrastructure, and reviews.