Head of AI Engineering - jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Head of AI Engineering based in Spain.

This role offers the opportunity to define and lead an organization-wide AI strategy, shaping how advanced technologies are adopted across engineering and business functions. You will build the foundations for scalable AI capabilities, from platform architecture and governance to practical AI-powered workflows. The position combines strategic leadership, technical expertise, and hands-on execution in a fast-moving technology environment. You will partner with engineering, security, product, analytics, and business teams to transform AI opportunities into reliable production solutions. You will establish standards, platforms, and operating models that enable teams to safely and effectively leverage AI. This opportunity is ideal for an AI leader who wants to build a long-term AI capability and drive measurable impact across an entire organization.

Accountabilities:

As a Head of AI Engineering, you will be responsible for defining the AI vision, building scalable AI capabilities, and enabling teams to adopt AI effectively across the organization. You will combine technical leadership, strategic thinking, and operational execution to create secure, reliable, and impactful AI solutions.

• Define and execute an AI strategy and roadmap focused on building AI capabilities as a core technology platform.
• Assess existing AI tools, vendors, internal solutions, costs, ownership models, risks, and unofficial AI usage across the organization.
• Establish an AI operating model, including ownership structures, initiative prioritization, experimentation processes, and production deployment standards.
• Design and implement AI platform architecture, including AI gateways, authentication, access controls, model routing, logging, cost management, usage tracking, and audit capabilities.
• Define and manage an approved AI technology ecosystem covering models, vendors, APIs, SaaS solutions, self-hosted components, and platform standards.
• Drive AI adoption across engineering productivity, code reviews, testing, automation, refactoring, support, analytics, product, and marketing workflows.
• Establish AI governance and security practices covering sensitive data, private repositories, credentials, production systems, compliance, and risk management.
• Implement AI observability and evaluation frameworks to monitor quality, reliability, latency, usage, costs, and return on investment.
• Create AI adoption programs, including training, internal champions, playbooks, and best practices for responsible AI usage.
• Build and lead an AI Engineering function with a scalable model combining centralized platform capabilities and domain-driven AI initiatives.