Requirements Proven experience as a CTO or founding engineer in a successful startup Experience scaling from 0-2 engineers to Series A/B 10 years of experience in software engineering Experience in enterprise software Strong record of managing remote engineering teams Experience leading complex enterprise or data platform deployments Pedigree from high-caliber companies Demonstrated ability to attract top talent Experience with executive teams and clients Job Description Seeking a CTO with 10 years in software engineering, AI/ML expertise, and startup scaling experience to lead a small team and shape company structure. The company is seeking a new lead engineer/CTO as a critical priority. The current team structure includes 3 senior engineers, 2 mid-level engineers, and a product designer joining soon. The new CTO will have the opportunity to hire 1-2 more engineers and will have the ability to shape the current structure. The role involves being the final decision maker for technical choices, with expertise in data and automation required. AI experience is critical, not just a background in ML. The CTO should be a talent magnet with a top pedigree from high-caliber companies and must attract top talent, ideally bringing 2 senior engineers. The role requires a strong communicator who is comfortable with executives and clients, and an architect-level engineer who can lead a small team. The company is looking for someone with 0-1 or 0-2 stage experience specifically. The compensation for the role is $300k USD plus 5% equity. The company is looking for proven experience as a CTO or founding engineer in a successful startup that scaled from 0–2 engineers to Series A/B, with 10 years of experience in software engineering, deep technical knowledge in data systems, AI/ML infrastructure, or enterprise software, and a strong record of managing remote engineering teams across geographies. The candidate should be an excellent communicator, fluent in English, and comfortable working with executive teams and clients, with experience leading complex enterprise or data platform deployments. A hybrid mindset, combining research-driven innovation with practical, product-oriented engineering, is also desired.