Falahly is an AI-powered job matching platform for the MENA (Middle East and North Africa) region. It uses vector embeddings and skill ontology matching to connect job seekers with relevant positions in UAE, Saudi Arabia, Egypt, Qatar, Kuwait, Bahrain, and beyond.

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Falahly covers the full MENA region including UAE (Dubai, Abu Dhabi), Saudi Arabia (Riyadh, Jeddah), Egypt (Cairo), Qatar (Doha), Kuwait, Bahrain, Jordan, Oman, Lebanon, Morocco, and Tunisia.

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Employers can post jobs and access Falahly's candidate database through the Employer portal at https://falahly.com/employers. Contact us at support@falahly.com for enterprise plans and bulk posting options.

How do I apply for the AI Technical Governance job at Gibraltar Technologies LLC ?

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Where is the AI Technical Governance position located?

This AI Technical Governance role is based in Dubai, United Arab Emirates.

AI Technical Governance

🏢 Gibraltar Technologies LLC

📍 Dubai, United Arab EmiratesContractOn-site

📅 Posted: 1w ago🔄 Updated: 6d ago

CV%

✨ AI Summary

Gibraltar Technologies LLC is seeking an experienced AI Technical Governance & Delivery Lead for a contract position in Dubai, UAE. This role involves providing technical leadership and governance across enterprise AI initiatives, including Generative AI, Machine Learning, and AI Agents. Responsibilities include governing technical delivery, reviewing solution architectures, ensuring adherence to standards, and providing technical direction. The ideal candidate will have a Bachelor's or Master's degree with 8-12 years of experience in solution architecture and AI solutions, with hands-on experience in Generative AI, LLMs, RAG, and AI Agents. Familiarity with cloud platforms like Azure, OCI, AWS, or GCP, and experience in regulated environments are desirable. The role requires strong collaboration skills with architects, engineering teams, cybersecurity, and business stakeholders. AI Technical Governance & Delivery LeadJob OverviewWe are looking for an experienced AI Technical Governance & Delivery Lead to provide technical leadership, architecture governance, and delivery oversight across multiple enterprise AI initiatives and development squads.The role will be responsible for governing AI technical delivery, reviewing and approving solution architectures, ensuring adherence to enterprise technology standards, and providing technical direction across Generative AI, Mach

Required Skills

Information Technology

○AI Governance○Machine Learning○RAG○Large Language Models○Generative AI○AI Agents○Data Architecture○Cloud Computing○Enterprise Applications○MLOps○LLMOps○Cybersecurity○Enterprise Architecture○Solution Architecture○Storage Solutions○Data Platforms○Scalability○Cloud Security○API Development○Cloud Architecture○Solution Design○DevOps○Reliability Engineering○AI Integration○REST API○Data Engineering & Analytics○TestNG○Test Environments○IT Infrastructure○CI/CD○Monitoring○Observability○Azure○AWS○OCI○GCP○Data Governance○System Integrations

Other

○Responsible AI○enterprise technology○delivery oversight○enterprise technology standards○technical direction○production-ready○business objectives○technical delivery○implementation approaches○technology standards○delivery methodologies○technical progress○delivery milestones○dependencies○risks○production readiness○mitigation actions○internal delivery teams○external delivery teams○approved architectures○roadmaps○best practices○enterprise AI platforms○maintainability○technology ecosystems○architectural direction○technical guidance○architecture decisions○enterprise technology strategy○technical lead○AI delivery squads○developers○AI engineers○ML engineers○architecture reviews○design workshops○technical assurance sessions○cross-team technical dependencies○delivery challenges○technical delivery practices○implementation○deployment practices○cloud-based AI environments○AI implementations○security controls○AI model risks○auditability○technical assurance reviews○deployment readiness assessments○AI-related risks○technical status○recommendations○technical insights○business stakeholders○technology teams○delivery partners○technical contributions○external vendors○strategic technology decisions

Business, Sales & Management

○HR Management○Marketing Analytics○Performance Management○Quality Standards○Instructional Design○Change Management○SAFe○Risk Management

Soft Skills & Professional Competencies

○Leadership○Initiative○Decision Making○Data Analysis○Planning

Finance, Legal & Governance

○IT Governance○Tax Compliance○Data Protection & Privacy○Regulatory Compliance

Engineering, Construction & Trades

○Mechanical Design○Process Engineering○CAPA

Education & Training

○Adult Learning Principles

Requirements

Description

AI Technical Governance & Delivery LeadJob OverviewWe are looking for an experienced AI Technical Governance & Delivery Lead to provide technical leadership, architecture governance, and delivery oversight across multiple enterprise AI initiatives and development squads.The role will be responsible for governing AI technical delivery, reviewing and approving solution architectures, ensuring adherence to enterprise technology standards, and providing technical direction across Generative AI, Machine Learning, AI Agents, RAG, analytics, and AI platforms.The successful candidate will work closely with solution architects, AI engineers, developers, data engineers, cloud and security teams, vendors, and senior stakeholders to ensure AI solutions are scalable, secure, compliant, production-ready, and aligned with enterprise architecture and business objectives.Key Responsibilities1. Technical Delivery GovernanceGovern technical delivery activities across multiple AI development squads.Review solution architectures, technical designs, and implementation approaches.Ensure consistency in architecture, engineering practices, technology standards, and delivery methodologies.Track technical progress, delivery milestones, dependencies, risks, and production readiness.Identify technical risks and drive appropriate mitigation actions.Review and approve solution designs prior to implementation and production deployment.Govern internal and external delivery teams to ensure adherence to approved architectures, technical standards, and roadmaps.2. Solution Architecture LeadershipDefine and establish enterprise AI solution architecture standards, principles, and best practices.Review and validate AI architectures covering LLMs, RAG, AI Agents, Machine Learning, analytics, and enterprise AI platforms.Ensure AI solutions meet requirements for scalability, maintainability, performance, reliability, and security.Govern integration approaches with enterprise applications, data platforms, APIs, and technology ecosystems.Provide architectural direction and technical guidance for complex AI initiatives.Challenge and validate architecture decisions to ensure alignment with enterprise technology strategy.3. Squad Leadership & Technical CoordinationAct as the technical lead across multiple AI delivery squads.Provide technical direction to solution architects, developers, AI engineers, ML engineers, and data engineers.Facilitate technical decision-making, architecture reviews, design workshops, and technical assurance sessions.Resolve cross-team technical dependencies, risks, and delivery challenges.Establish engineering quality standards and technical delivery practices.Ensure consistency in design, implementation, integration, testing, and operational readiness across AI initiatives.4. AI Platform & Environment OversightGovern the utilization of AI platforms, development environments, and deployment practices.Ensure AI solutions align with cloud, infrastructure, cybersecurity, data, and enterprise architecture standards.Review MLOps/LLMOps, CI/CD, monitoring, observability, model lifecycle management, and operational support capabilities.Ensure AI solutions are production-ready, scalable, supportable, and aligned with enterprise operational requirements.Provide technical oversight of cloud-based AI environments across platforms such as Azure, AWS, OCI, or GCP.5. Quality, Security & ComplianceEnsure AI implementations comply with enterprise technical governance and security controls.Review AI model risks, performance metrics, reliability, and operational safeguards.Ensure implementation of Responsible AI, privacy, security, auditability, and regulatory requirements.Lead technical assurance reviews and deployment readiness assessments.Collaborate with cybersecurity, data governance, risk, and compliance teams to address AI-related risks.6. Stakeholder & Vendor ManagementCommunicate technical status, architecture decisions, risks, dependencies, and recommendations to senior leadership.Provide technical insights and recommendations within project and technology governance forums.Work closely with business stakeholders, enterprise architects, technology teams, vendors, and delivery partners.Govern technical contributions from external vendors and system integrators.Support strategic technology decisions and AI roadmap planning.QualificationsBachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, Information Technology, or a related discipline.Strong understanding of Generative AI, Machine Learning, AI Agents, RAG architecture, cloud platforms, and enterprise application architecture.Relevant certifications in Enterprise Architecture, Cloud, Artificial Intelligence, Azure, AWS, OCI, GCP, or equivalent technologies are preferred.Knowledge of Responsible AI, AI governance, MLOps/LLMOps, cybersecurity, and enterprise architecture frameworks.Required Experience8–12 years of experience in solution architecture, technical delivery management, AI solutions, or enterprise technology environments.Proven experience leading technical delivery across multiple teams, projects, or AI development squads.Strong experience designing, reviewing, and governing enterprise solution architectures.Hands-on or strong practical experience with Generative AI, LLMs, RAG, AI Agents, Machine Learning, and enterprise AI platforms.Experience reviewing solution designs and ensuring adherence to architecture, security, engineering, and delivery standards.Experience with cloud platforms such as Azure, OCI, AWS, or GCP.Experience managing technical dependencies, risks, issues, and delivery challenges across multiple teams and vendors.Experience working within government, public sector, financial services, healthcare, telecom, or other regulated environments is highly desirable.Experience governing enterprise AI implementations and technical delivery programs.Strong experience collaborating with architects, engineering teams, cybersecurity, infrastructure, data, and business stakeholders.

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