About the Role This is a founding engineering role at an early-stage data infrastructure company, working directly with the CTO to build core systems for extracting, analyzing, and visualizing web data at scale. You'll own significant pieces of the product — from autonomous agents to distributed backend services — powering enterprise customers who depend on structured, real-world web data every day. What You'll Do Build autonomous agents that solve complex, real-world information extraction problems across diverse and unpredictable web environments. Design and iterate on a full-stack, self-serve application that makes sophisticated workflows intuitive for non-technical users. Maintain and scale backend architecture to reliably process thousands of requests per second and tens of millions of rows of data daily. Contribute broadly across the stack — infrastructure as code, ML pipelines, website updates, and whatever else keeps the team moving fast. What We're Looking For 5+ years of experience shipping production software, or equivalent demonstrated skill in a 0→1 environment. Proven track record launching meaningful products on small, early-stage teams with rapid iteration cycles. Hands-on experience building LLM applications and agentic systems, including RAG, model evaluation, and fine-tuning. Experience designing and maintaining high-scale distributed backend systems (thousands of RPS, millions of data rows daily). Full-stack capability spanning backend, frontend, and infrastructure layers. Proficiency with infrastructure as code and deployment automation. Deep domain expertise in antibot systems, reverse engineering, JavaScript deobfuscation, or browser automation is a strong plus. Experience with web scraping, data extraction, or web automation at scale is a strong plus. A bias toward action and comfort with the pace and ambiguity of an early-stage startup. Preference for in-person, collaborative work with a tight-knit team. Compensation & Benefits Salary range: $170,000 – $220,000 USD annually. Visa sponsorship is available. Location On-site in New York City, NY . In-person attendance is expected.
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