Chief Technology Officer - Artificial Intelligence/Machine Learning

Job Summary

Roles And Responsibilities

Technology Leadership & Vision :

• Define and own the technology roadmap aligned with business goals and scaling strategy.
• Lead architectural modernization, platform migration, and integration of AI, ML, and automation technologies.
• Drive innovation and ensure the product is built on scalable, secure, and future-proof technology.
  

Team Building & Execution

• Build and mentor a high-performing engineering team with a strong culture of agility, ownership, and performance.
• Establish modern engineering best practices and delivery frameworks across product, DevOps, and QA.
• Set KPIs and drive velocity, code quality, and accountability across teams.
  

Product & Business Partnership

• Partner closely with product, sales, and customer success teams to improve customer experience and retention.
• Translate market needs into platform capabilities and drive faster release cycles and product improvements.
• Evaluate and integrate third-party solutions or acquisitions as part of growth and expansion strategies.
  

Strategic Scaling & Portfolio Growth

• Implement data-driven systems and scalable architectures for global SaaS growth.
• Support future fundraising, due diligence, and strategic acquisitions with strong tech narratives.
• Be open to taking on additional CTO/Tech Advisor roles across other SaaS companies in the portfolio as needed.
  

Must-Haves

SKILLS AND QUALIFICATIONS :

• 1724 years of total experience with at least 810 years in senior technology leadership roles in SaaS businesses.
• Proven experience in scaling a B2B SaaS company from early to growth stage (0100 journey or founder/CTO experience).
• Deep understanding of SaaS architecture, cloud platforms (AWS/GCP), multi-tenant systems, and security standards.
• Strong knowledge of modern engineering practices including CI/CD, DevOps, and Agile delivery.
  

Preferred/Bonus

• Experience in founding or co-founding a SaaS product company.
• Exposure to applied AI/ML, LLMs, automation, or data platforms in a SaaS context.
• Previous experience working with PE/VC-backed companies or in turnaround scenarios.
• Entrepreneurial mindset with high ownership and bias for execution.