Chief Technology Officer (CTO)

Role summary

[Company] is hiring a Chief Technology Officer to lead technology innovation and engineering for responsible AI. Reporting to the [CEO / President], you will define the technology vision, build secure and scalable AI platforms, and embed governance into how systems are designed, deployed, and monitored. This role sits at the intersection of engineering, product, security, and AI governance, and is a strong fit for a technology leader who can turn ideas into trustworthy systems at enterprise scale.

Key responsibilities

• Technology strategy and innovation. Define the organization's technology vision and roadmap to drive innovation, support AI adoption, and align with business strategy.
• AI architecture and platforms. Design and oversee modern, secure, and scalable architectures and platforms that enable AI, data, and digital solutions.
• Model development and deployment. Lead the development, deployment, and lifecycle management of machine learning models and AI applications with quality, reliability, and safety.
• Emerging technology evaluation. Research and evaluate emerging technologies, tools, and frameworks to identify high-value opportunities and manage technology risk.
• AI engineering standards and best practices. Establish engineering standards, MLOps practices, code quality, governance controls, and testing frameworks to ensure ethical and reliable AI by design.
• Responsible AI by design. Embed ethics, fairness, privacy, transparency, and security into the technology lifecycle from design through deployment and monitoring.
• Scalability and performance. Ensure technology solutions are scalable, resilient, secure, and optimized to support enterprise growth and AI workloads.
• Innovation leadership and collaboration. Partner with executives, product, engineering, security, legal, compliance, and data teams to deliver responsible AI innovation across the enterprise.

Required qualifications

• [10 to 15] years in software engineering or technology leadership, including [5 or more] years leading engineering organizations at the director level or above.
• Proven record designing and operating secure, scalable cloud and platform architectures that support production AI or data workloads.
• Hands-on understanding of the machine learning lifecycle, from data engineering and model development through deployment, monitoring, and MLOps.
• Experience embedding security, privacy, and governance controls into engineering practice, aligned to frameworks such as [NIST AI RMF / ISO/IEC 42001 / SOC 2 / your stack].
• Executive communication skills, with a track record of partnering across product, security, legal, and the business.

Preferred qualifications

• Experience delivering AI or machine learning products in a regulated industry such as [financial services / healthcare / insurance / public sector].
• Familiarity with EU AI Act readiness, model documentation standards, or algorithmic impact assessments.
• Background scaling engineering teams through [hypergrowth / a major platform migration / a zero-to-one build].
• Advanced degree in computer science, engineering, or a related field, or equivalent practical experience.

About the team

[Describe the team in two or three sentences: the size and shape of the engineering organization, how mature the AI platform and governance program are, and what the first year looks like. Technology leaders respond to honesty about scope, so say whether this is a build, a turnaround, or scaling an established function.]

[Salary range. Postings with salary ranges perform significantly better on GRC Careers, and several states require them.]