Head of Internal Technology and AI

Riyadh, Saudi Arabia

Full time

Hybrid

Job description

About Ektis

Ektis is a boutique financial services consulting firm operating at the heart of the GCC's financial ecosystem. We partner with banks, fintechs, development finance institutions, and public-sector clients to solve their most critical challenges - spanning strategy, commercial growth, risk, payments, and transformation.

Role purpose

The Head of Internal Technology and AI leads Ektis's internal technology and AI function to enable the firm's growth across the GCC. The Head ensures that every internal function has the systems, tools, data and technical support needed to operate effectively. The role is accountable for improving operational efficiency, maintaining reliable services and building the internal capability to support a growing business.

Working with internal teams, the Head identifies delays, duplication and manual work, then delivers practical improvements through software, AI agents and automation. This includes maintaining a company-wide library of reusable AI skills and helping employees use approved tools in their daily work. Agents and workflows must be tested, scored and monitored against defined measures of accuracy, task completion, time saved and cost, with clear ownership and appropriate human oversight.

The role requires direct involvement in software engineering and oversight of the full development lifecycle, from business requirements and system design through implementation, testing, deployment and maintenance. The Head ensures that business applications, integrations, cloud infrastructure and data support the needs of internal functions, with clear service standards, dependable reporting and tested arrangements for incident response, backup and recovery.

The Head builds and leads the internal IT team as Ektis grows, setting responsibilities, developing staff and managing external providers. This includes oversight of employee support and the full lifecycle of laptops and other technology assets, including Microsoft Intune and mobile device management. The Head also establishes AI and technology governance, defines security requirements and ensures that controls, access rights, risks and corrective actions are managed through assigned owners.

The role controls technology expenditure across cloud services, AI usage, software licences, devices and suppliers. Investment and procurement decisions must reflect business priorities and the full cost of implementation, operation and support. The Head is expected to reduce avoidable expenditure, match capacity to demand and demonstrate efficiency gains while maintaining agreed service and security standards.

Key responsibilities

1. AI enablement

Maintain a prioritised AI delivery plan with defined business problems, owners, budgets, milestones and expected improvements in time, cost or quality.

Maintain a company-wide library of reusable AI skills: documented instructions, tools and workflows for employees and agents. Assign an owner, version, test record and review date to each skill; update or retire it when requirements change.

Train employees to use approved AI tools and skills. Measure adoption, task completion time, error rates and human review effort against the process before implementation.

2. Agent development and evaluation

Design, build and maintain AI agents that automate defined tasks and integrate with internal systems. Define permitted data, tools and actions, execution and spending limits, and actions requiring human approval.

Maintain test cases with expected results. Score agents on accuracy, task completion, failure rate, control compliance, response time and cost per successful task.

Set pass criteria for release, investigate failed tests and monitor production results. Re-test after changes to models, skills, data or tools; define how an agent is stopped, corrected or handed to a person.

3. AI governance

Establish and maintain AI governance aligned with ISO/IEC 42001, covering approved tools, acceptable use, data handling, human oversight and accountability.

Maintain a register of AI applications and agents, with named owners, risk assessments, approval records and review dates.

Set controls for confidential information and model-provider access to company data. Investigate errors, inappropriate disclosure and other material failures, and track corrective action.

4. Software engineering

Lead the software development lifecycle from requirements and architecture through development, testing, deployment, support and retirement.

Set standards for code quality, version control, peer review, documentation and automated testing. Review architecture and production code, and contribute to implementation and fault resolution.

Separate development, test and production environments. Control integrations, dependencies and releases; require acceptance tests, monitoring, a support owner and a tested rollback procedure.

Maintain an application register and a prioritised plan to correct recurring defects, replace unsupported components and reduce maintenance effort.

5. Internal IT operations

Oversee daily IT services, employee support, cloud infrastructure, networks and business applications, including ERP, HR, CRM and collaboration systems.

Define service availability, support response and incident resolution targets. Monitor performance, investigate repeated incidents and track corrective work to completion.

Set recovery time and data recovery requirements for critical systems. Schedule backups, test restoration and plan infrastructure capacity and maintenance.

Assign owners to key business data, validate data transferred between systems and maintain documented definitions for management reports.

Work with HR to standardise the technology steps for onboarding, role changes and offboarding, including approvals, account setup, access changes, device allocation and recovery, and licence removal.

Support Finance in maintaining secure, reliable finance and ERP systems. Implement approved access permissions, segregation of duties, audit logging and controlled changes; monitor integrations and resolve technical issues affecting payroll, billing or financial reporting.

6. Device and asset management

Control the full lifecycle of laptops, mobile devices and other IT assets, from procurement and allocation to maintenance, replacement, recovery and secure disposal.

Maintain an asset register with serial numbers, assigned users, location, purchase cost, warranty and replacement dates. Reconcile issued, stored and returned equipment against the register.

Oversee Microsoft Intune and mobile device management (MDM), including device enrolment, configuration, application deployment, updates and compliance reporting.

Require device encryption, controlled administrator access and authorised remote lock or wipe procedures. Control device issue, access changes, account removal and equipment recovery when employees join, change roles or leave.

7. Security governance

Set security requirements for identity and access management, multi-factor authentication, privileged access, patching and endpoint protection. Review compliance and approved exceptions.

Review control effectiveness, security incidents and unresolved risks. Assign operational responsibilities to the IT team or qualified service providers, with escalation routes, remediation owners and completion dates.

Maintain technology controls and evidence aligned with ISO/IEC 27001. Support internal and external audits and approved certification programmes; assign findings to owners and verify corrective action.

Maintain technology policies, risk records and audit evidence. Address applicable data protection, residency and cloud requirements in the GCC markets where Ektis operates, with specialist advice where required.

8. Cost control

Prepare and manage technology budgets covering cloud, AI usage, software licences, devices, support and suppliers. Review actual spend against budget monthly; control purchase approvals, commitments and renewals.

Match cloud compute and storage capacity to demand. Remove idle resources, schedule non-production services, review retention and data transfer costs, and assess committed-spend agreements against actual usage.

Set AI usage budgets and alerts. Compare models, request volumes, caching and batching against tested quality, security and cost requirements.

Reclaim unused licences and assess equipment replacement and supplier renewals against actual need. Compare acquisition, integration, migration, support and running costs before technology purchases or changes.

Report budget variances, cost per employee, cost per successful AI task and realised savings, including implementation and support costs.

9. Team leadership

Build and lead the internal IT team as the business grows, defining responsibilities, recruitment priorities and the balance between internal capability and external support.

Set individual objectives, allocate support and project work, and maintain a skills development plan. Document operating procedures and cross-train staff for critical services.

Manage supplier performance and technical partnerships against agreed scope, service standards and cost.

Qualifications and experience

Essential

Bachelor of Science (BSc) in Computer Science.

10 to 14 years of technology experience, including software development, production system support and leadership of technical teams.

Experience taking software from requirements and architecture through coding, testing, deployment and maintenance. Able to review production code and explain design decisions.

Experience building agents integrated with business systems, maintaining versioned AI skills and using test datasets and scorecards to assess performance.

Experience leading employee IT support and asset management. Working knowledge of Microsoft Intune enrolment, configuration profiles, application deployment, device compliance and endpoint security controls.

Experience managing cloud capacity, licences, technology budgets and supplier contracts, with examples of cost reductions that maintained service quality.

Ability to define AI approval and oversight controls, assess access and data protection risks, and review security incidents and remediation plans.

Experience in Saudi Arabia or the wider GCC applying data protection, residency and cloud requirements to technology decisions.

Fluent English, with the ability to explain technical decisions, costs and risks clearly.

Preferred

Experience supporting the internal technology needs of a professional services or consulting firm, including operations across multiple GCC markets.

Experience implementing controls, preparing audit evidence and closing findings for ISO/IEC 27001 information security management or ISO/IEC 42001 AI management systems.

Experience supporting finance, ERP and HR systems, including access controls, segregation of duties, audit logging and secure integrations.

Experience automating employee onboarding, role changes and offboarding with HR, including device allocation, access approvals, licence management and equipment recovery.

Professional certification in cloud administration or architecture, software engineering, AI engineering, IT service management, or ISO/IEC 27001 or ISO/IEC 42001 implementation or auditing.

Arabic reading, writing and speaking skills are strongly preferred.

Measures of success

Performance is assessed against agreed baselines ,targets and review dates, using service records, financial data, control evidence and feedback from internal functions.

Operational efficiency: Internal processes show measurable reductions in manual effort, processing time, rework and errors. Improvements are confirmed with the function using the process and sustained after implementation.

AI adoption and performance: Approved AI tools are used in their intended workflows. Agents meet accuracy, task completion, control compliance and cost criteria; reusable skills have current owners, versions, tests and review dates.

ISO governance: Technology and AI controls within the agreed ISO/IEC 27001 and ISO/IEC 42001 scope are documented and supported by evidence. Audits and management reviews take place as scheduled; findings are closed by agreed dates and any approved certification milestones are met.

AI governance: AI applications and agents are registered, assessed and approved before use. Data access, human oversight and material changes follow approved controls; failures and exceptions are recorded, investigated and resolved by assigned owners.

Security maintenance: Patching, endpoint protection, access reviews and vulnerability remediation meet deadlines set according to risk. Unsupported components have replacement plans; overdue security issues are escalated and corrective actions are verified.

Service reliability and recovery: Critical systems meet agreed availability, support response and incident resolution targets. Backup restoration and recovery tests demonstrate that services and data can be restored within agreed time and data loss limits.

Software delivery: Releases pass acceptance and security checks, have a support owner and include a tested rollback procedure. Delivery commitments are met, recurring defects decline and maintenance work is completed against the agreed plan.

Asset control and maintenance: Asset records reconcile with equipment held and issued. Devices meet Intune and security requirements; maintenance, warranty and replacement schedules are current, and repairs, returns and secure disposal are documented.

HR onboarding and offboarding: New employees have approved devices, applications and access ready for their agreed start date. Role changes are reflected in permissions; leaver access and active sessions are revoked at the authorised time, licences are reclaimed and equipment is recovered or recorded as an outstanding exception.

Finance systems: Finance and ERP systems meet agreed availability and data integrity requirements. Access, segregation of duties, audit trails and system changes follow controls agreed with Finance; technical issues affecting payroll, billing or financial reporting are resolved within agreed deadlines.

Budget control: Actual spending and committed costs remain within approved budgets. Forecasts and variances are reviewed monthly, with corrective action where required. Reported savings include implementation and support costs and use comparable service levels and demand.

Cloud and licence efficiency: Cloud capacity, AI usage and software licences match business demand. Idle resources and unused subscriptions are removed; cost per employee and per successful AI task meet agreed efficiency targets without weakening service quality or security.

Team and supplier performance: Staffing, training and support coverage meet the agreed service plan. Critical procedures are documented and supported by trained cover; suppliers meet contractual service and cost commitments, with performance issues addressed by agreed dates.

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