Zintellix is an AI-driven B2B SaaS platform that empowers e-commerce businesses with real-time, actionable analytics. We help brands and marketplaces unlock the full potential of their data through advanced AI models, automated insights, and predictive intelligence. Our mission is to redefine how modern e-commerce companies make data-backed decisions at scale. Role Overview We’re seeking a visionary Chief Technology Officer (CTO) to lead the technology strategy and execution at Zintellix. The ideal candidate is a product-minded, hands-on leader who has scaled SaaS platforms, built data-centric products, and is deeply passionate about AI/ML, data engineering, and delivering customer-centric solutions. You will work closely with the founders, product, and growth teams to shape our technical roadmap, build scalable systems, and drive innovation that keeps Zintellix at the forefront of AI analytics for e-commerce. Key Responsibilities Technology Strategy: Define and execute the company’s technical vision and long-term architecture to support growth, scalability, and innovation. Team Leadership: Build, lead, and mentor a high-performing engineering, data science, and DevOps team. Product Development: Oversee end-to-end development of the Zintellix platform, from data ingestion pipelines to AI-driven insight generation and dashboard delivery. AI & Data Infrastructure: Lead the development of our AI/ML models and data infrastructure (ETL pipelines, data lakes/warehouses, real-time analytics). Security & Compliance: Ensure robust data governance, security practices, and compliance with regulations (e.g., GDPR, SOC 2). Cross-functional Collaboration: Work closely with product, design, and business stakeholders to align technology with customer needs. Scalability: Architect for reliability, performance, and scalability to serve large e-commerce enterprises and marketplaces. Innovation: Stay ahead of emerging technologies (e.g., GenAI, LLMs, AutoML) and evaluate their strategic relevance to Zintellix. Required Qualifications Proven experience (8+ years) in leading engineering or technology teams at high-growth SaaS or analytics companies. Deep expertise in cloud-native architecture (AWS, GCP, or Azure), distributed systems, and microservices. Hands-on experience with modern data stacks (Snowflake, DBT, Airflow, Kafka, etc.). Strong understanding of AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and deployment of production-grade models. Prior experience working on B2B platforms, ideally with experience in e-commerce, retail, or martech analytics. Excellent leadership, communication, and stakeholder management skills. Startup experience and ability to thrive in a fast-paced, iterative environment. Preferred Qualifications Experience scaling a platform from 0 to 1 and beyond. Familiarity with LLMs, vector databases (e.g., Pinecone, Weaviate), and AI-powered insight generation. Exposure to self-serve BI tools, customer-facing dashboards, and real-time data systems. Entrepreneurial mindset and previous experience as a technical co-founder or founding engineer. What We Offer Competitive salary + equity Opportunity to shape the future of an AI-first SaaS platform A collaborative, transparent, and growth-oriented team culture Flexible remote/hybrid working options Chance to work at the intersection of e-commerce, AI, and analytics Show more Show less

A fast-growing tech startup is seeking a highly motivated and skilled Data Engineer to join our team. We are solving the problem of ecommerce and looking for someone who is passionate about using data to drive business decisions. Responsibilities: Good to have: Big Data/Hive, Hadoop, Airflow, AWS Glue, AWS S3, AWS Redshift , Pyspark/Python, SQL Ability to write Glue ETL code using Pyspark/Phython Must have experience in ETL/Big Data development Exposure to CI/CD processes. Familiar with Data Warehouse. Hands-on Orchestration Tools like Apache Airflow. Design, develop, and maintain data pipelines to gather and process large amounts of ecommerce data. Collaborate with cross-functional teams to understand data requirements and design solutions that meet their needs. Implement and maintain data security, performance, and quality assurance measures. Build data models and algorithms to support data-driven decision making. Participate in code and design reviews to ensure high-quality standards are met. Troubleshoot and debug data issues and provide technical support to internal teams and clients. Stay up-to-date with emerging trends and technologies in data engineering. Requirements: Bachelor's degree in Computer Science or related field. Proficiency in Python, SQL, and other programming languages. Strong knowledge of data warehousing, data modeling, and ETL processes. Previous internship in AI saas based companies Experience with cloud-based data storage and processing technologies (e.g. AWS, GCP, or Azure). Familiarity with NoSQL databases and distributed systems. Strong communication and collaboration skills. Show more Show less