Job
Description
Role Overview As CTO, you’ll lead the entire technology function — from product architecture to team management. You’ll work directly with the founders, guiding product evolution, scaling the backend, and delivering seamless user experiences powered by data. Tech Stack Frontend: Next.js Backend: Node.js (REST/GraphQL APIs) Databases: MySQL, Redis (for caching, queueing, real-time performance) Key Responsibilities Define and lead the tech strategy, architecture, and execution roadmap of a SAAS Product. Build and scale modular, maintainable, and secure backend infrastructure . Oversee frontend performance , UX stability, and modern best practices in React/Next.js. Own data management and real-time processing pipelines using MySQL and Redis. Design and maintain high-availability, fault-tolerant systems for fast-growing user traffic. Collaborate closely with the founders, PPC team, and UI/UX to bring value-driven features to market. Establish coding standards, documentation practices, and dev workflows (CI/CD, Git, automated testing). Mentor and grow the internal dev/design team while hiring top engineering talent. Keep a pulse on modern tools (AI, LLMs, auto-optimization APIs, etc.) that can enhance platform intelligence. Required Experience 8+ years of overall software development experience. Minimum 3 years in a senior leadership role (CTO, VP Engineering, or equivalent). Proven experience in building and scaling SaaS products — ideally in AdTech, MarTech, or Analytics. Deep expertise in: Node.js , RESTful/GraphQL APIs Next.js/React , component architecture, SSR/CSR MySQL , DB optimization, migrations, data design Redis , caching layers, pub-sub, and queueing systems Strong understanding of cloud infrastructure (AWS/GCP) , CI/CD , and DevOps pipelines . Familiarity with building scalable analytics engines, campaign tracking, or real-time alerting systems. Excellent problem-solving, communication, and leadership skills. Nice-to-Have Experience with Google Ads / Meta Ads APIs Background in AI/ML integrations for recommendations/automation Previous startup or early-stage product experience Exposure to data visualization libraries , dashboards, or performance scorecards
