Head of AI, Automation & Analytics

As Head of AI & Automation, you will lead the strategy, development, and implementation of AI-powered solutions, workflow automation, and analytics across a global technology organization. You will manage a specialized technical team responsible for building intelligent systems, streamlining operations, and improving productivity across multiple departments. Combining strategic leadership with technical expertise, you will oversee the development of AI agents, automation platforms, and enterprise-wide integrations. You will also establish robust governance, security, and reliability standards to ensure that all solutions are scalable and compliant. Working closely with executive leadership, engineering, security, and business teams, you will identify opportunities to eliminate repetitive work and deliver measurable operational value. This is an exciting opportunity to shape an organization's AI transformation while building high-impact technology capabilities in a remote-first environment.

• Define and lead the AI and automation function's strategy, operating model, and rolling six-month roadmap, ensuring alignment with executive priorities and organizational objectives.

• Establish quarterly objectives and key results (OKRs), monitor progress, and communicate performance and strategic outcomes to steering committees and executive leadership.

• Identify, evaluate, and prioritize business processes suitable for automation and AI implementation, considering potential business impact, time savings, efficiency gains, and operational risks.

• Own the roadmap and continuous development of the organization's internal AI assistant, connecting company knowledge, data, and tools through a unified interface.

• Lead, mentor, and develop a multidisciplinary AI and automation team, including defining responsibilities, managing performance, planning team structure, and recruiting new talent.

• Oversee delivery operations through structured sprint cycles, prioritization frameworks, and capacity planning that balance strategic projects, incoming requests, continuous improvement, and operational support.

• Define technical architecture and development standards for AI agents, retrieval-augmented generation (RAG), Model Context Protocol (MCP) integrations, and workflow automation.

• Review technical designs and production readiness of solutions built using Google Cloud technologies, including Vertex AI, BigQuery, and Google Kubernetes Engine (GKE), as well as n8n.

• Lead the delivery of complex, cross-functional automation projects spanning multiple departments and systems, including employee onboarding and offboarding workflows.

• Establish and enforce production automation standards covering system ownership, error monitoring, alerting, code quality, documentation, and least-privilege access.

• Regularly audit automation platforms, identify governance or reliability gaps, and coordinate remediation initiatives.

• Collaborate with Cloud Platform Engineering, IT, and Security teams to ensure appropriate hosting, access management, infrastructure security, and incident response procedures.

• Conduct AI risk assessments as part of vendor procurement, evaluating AI usage, data handling practices, security implications, and contractual requirements.

• Manage relationships with external technology providers and oversee the function's tooling ecosystem, including n8n, AI model providers, and Google Cloud AI services.

• Act as the central point of contact for AI, automation, and analytics requests, ensuring every request is properly assessed, assigned, and managed through a transparent intake process.

• Partner with department leaders to understand existing workflows, identify improvement opportunities, and determine which solutions should be delivered centrally or enabled within individual teams.

• Drive internal adoption through clear documentation, communication, and training initiatives in collaboration with the AI and Automation Enablement Lead.

• Measure success through operational efficiency gains, cost and time savings, platform adoption, automation reliability, request ownership, and organizational awareness of available services.

• Bachelor's degree in Software Engineering, Computer Science, Cybersecurity, or a related technical discipline.

• Several years of professional experience in cloud infrastructure, security engineering, and automation, including designing and managing production systems on Google Cloud.

• Strong working knowledge of large language models (LLMs), AI agents, retrieval-augmented generation (RAG), and the Model Context Protocol (MCP).

• Practical experience with Infrastructure as Code (IaC), particularly Terraform, as well as containers, Kubernetes, and Identity and Access Management (IAM).

• Proven experience leading and developing technical teams, establishing strategic roadmaps, defining OKRs, and reporting results to senior executives.

• Strong understanding of workflow automation, operational efficiency, and the opportunities and risks associated with implementing AI across business functions.

• Ability to identify repetitive, low-value activities and design secure, scalable solutions that improve productivity and reduce operational overhead.

• Experience managing multiple projects and stakeholder groups simultaneously, with strong prioritization, coordination, and problem-solving capabilities.

• Excellent written and verbal communication skills, with the ability to explain technical decisions, risks, and trade-offs clearly to both technical and non-technical audiences.

• Strong stakeholder management skills and the confidence to challenge existing approaches, communicate ideas diplomatically, and contribute constructively to strategic discussions.

• Comfortable working in a culture that values radical candour, emphasizing transparency, respectful feedback, accountability, and openness to different perspectives.

Additional qualifications that would be an advantage:

• Relevant certifications in cloud infrastructure, cybersecurity, or artificial intelligence, particularly Google Cloud certifications.

• Experience working in enterprise technology environments, especially in roles supporting internal business stakeholders.

• Background in security operations, risk management, or compliance frameworks such as SOC 2, with practical experience applying governance principles to AI and automation systems.