CTO

We are looking for a hands-on, technology-driven Chief Technology Officer (CTO) to lead our technology strategy, product engineering, AI development, cloud infrastructure, and data engineering initiatives. The ideal candidate will combine strong technical expertise with engineering leadership and the ability to build scalable, secure, production-ready AI products.

Key Responsibilities

1. Technology Strategy & Leadership

Define and execute the company's technology vision, architecture, and engineering roadmap in alignment with business goals.

Lead end-to-end product development, from technical design and prototyping to deployment, monitoring, and continuous improvement.

Make strategic decisions regarding technology stacks, architecture, cloud platforms, databases, and AI frameworks.

Build scalable, maintainable, secure, and cost-efficient technology systems.

Work closely with the founder and business teams to translate product requirements into technical solutions.

Establish engineering standards, coding practices, documentation, and development processes.

1. AI Engineering & Generative AI

Lead the development and deployment of AI-powered applications, AI agents, LLM-based systems, and intelligent analytics solutions.

Design and implement RAG architectures, vector search, embeddings, semantic search, and knowledge retrieval systems.

Work with LLM providers, open-source models, model APIs, and agent frameworks to build production-grade AI products.

Develop AI agents capable of analyzing data, generating insights, answering business questions, and supporting workflow automation.

Implement prompt engineering, model evaluation, guardrails, observability, and AI quality monitoring.

Optimize AI application performance, inference costs, latency, reliability, and scalability.

Explore agentic workflows, MCP integrations, tool calling, and multi-agent architectures where appropriate.

1. Data Engineering & Analytics

Architect and build scalable data pipelines, ETL/ELT workflows, and data integration frameworks.

Design data platforms that connect e-commerce, CRM, ERP, marketing, marketplace, and business intelligence systems.

Work with SQL and NoSQL databases, data warehouses, lakehouse architectures, and analytical data models.

Lead the development of data ingestion, transformation, validation, orchestration, and monitoring systems.

Establish data quality, governance, access control, and metadata management practices.

Optimize analytical queries, reporting pipelines, and large-scale data processing.

Build reliable data foundations for AI-powered analytics, natural-language querying, and automated business intelligence.

1. Cloud Infrastructure & DevOps

Design and manage scalable cloud infrastructure using AWS or other major cloud platforms.

Lead cloud architecture, deployment automation, infrastructure optimization, and production reliability.

Implement CI/CD pipelines, Infrastructure as Code (IaC), containerization, and automated testing.

Work with Docker, Kubernetes or managed container services, serverless architecture, and cloud-native services as appropriate.

Establish monitoring, logging, alerting, disaster recovery, backup, and incident management processes.

Optimize cloud infrastructure costs, resource utilization, application performance, and availability.

Implement secure secrets management, identity and access management, and network security.

1. Software Architecture & Product Engineering

Oversee the architecture and development of scalable SaaS applications and multi-tenant platforms.

Lead backend API development, database design, frontend integrations, and third-party system connectivity.

Work with modern technologies such as React, TypeScript, Python, Node.js, FastAPI, and relevant frameworks.

Ensure application security, performance, reliability, maintainability, and code quality.

Establish code review standards, automated testing, release management, and version control practices.

Guide the development of APIs, integrations, SDKs, and developer-facing capabilities.

1. Engineering Team Leadership

Lead and mentor developers, AI engineers, data engineers, and DevOps professionals.

Establish sprint planning, technical reviews, delivery milestones, and engineering KPIs.

Review system architecture, pull requests, implementation plans, and critical technical decisions.

Build a culture of ownership, accountability, experimentation, and continuous learning.

Support technical hiring, team development, and engineering resource planning.

Collaborate with product, sales, and business teams to prioritize features based on customer needs and commercial impact.

1. Security, Reliability & Governance

Establish secure software development practices and data protection controls.

Implement appropriate authentication, authorization, tenant isolation, encryption, and audit logging.

Ensure responsible AI practices, data privacy, and appropriate safeguards for AI-generated outputs.

Define service-level objectives, incident response processes, and production-readiness standards.

Support relevant customer security requirements and compliance initiatives.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5–8 years of experience in software engineering, AI engineering, cloud infrastructure, data engineering, or technology leadership.
• Strong hands-on programming skills in Python, TypeScript/JavaScript, or another relevant language.
• Proven experience designing and deploying production-grade software applications and scalable architectures.
• Strong understanding of Generative AI, LLMs, RAG, AI agents, and AI application development.
• Experience building data pipelines, integrating APIs, and working with SQL databases and analytical systems.
• Practical experience with AWS, Azure, or Google Cloud Platform.
• Familiarity with Docker, CI/CD, cloud deployment, monitoring, and infrastructure automation.
• Strong understanding of REST APIs, distributed systems, application security, and system design.
• Experience making architecture decisions, solving complex technical problems, and guiding engineering teams.
• Excellent communication, decision-making, project planning, and stakeholder management skills.

Preferred Experience

Experience working in a B2B SaaS, AI startup, product engineering company, or cloud technology organization.

Experience taking an AI or SaaS product from prototype to production.

Experience building multi-tenant SaaS architecture and enterprise-grade integrations.

Experience with AI-powered analytics, business intelligence, e-commerce data, or enterprise data platforms.

Familiarity with agentic AI, tool calling, MCP servers, and automated business workflows.

Experience managing cloud costs, LLM usage costs, system reliability, and engineering delivery.

A strong hands-on approach, with the ability to write and review code rather than relying exclusively on people management.

Key Performance Indicators (KPIs)

• Product delivery speed and engineering execution.
• Reliability, availability, and performance of production systems.
• Quality and accuracy of AI-powered features.
• Data pipeline reliability, freshness, and data quality.
• Cloud infrastructure and LLM cost optimization.
• Security, scalability, and maintainability of the technology platform.
• Successful delivery of product milestones and customer requirements.
• Engineering team productivity, code quality, and operational efficiency.

What We Offer

• An opportunity to lead technology strategy at an AI-driven SaaS company.
• Ownership of AI, data engineering, cloud infrastructure, and product architecture.
• Direct collaboration with the founder on product vision and technical strategy.
• The opportunity to build and scale production-grade AI products and intelligent agents.
• A high-ownership, innovation-focused startup environment.
• Career growth with the opportunity to shape the company's long-term technology direction.