AI/ML Technical Architect Lead

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML Technical Architect Lead based in United Arab Emirates. This is a senior, hands-on technical leadership role focused on transforming advanced AI and machine learning capabilities into secure, scalable, production-ready solutions. You will shape AI/ML strategy and architecture while directly contributing to model development, deployment, integration, and operationalization. The role combines solution architecture, software engineering, MLOps, cybersecurity, and responsible AI practices. You will work on complex decision-support, automation, and predictive analytics initiatives in highly regulated environments. You will also guide cross-functional teams, advise senior stakeholders, and help move innovative prototypes into reliable operational systems. The position offers the opportunity to work with modern technologies including AWS, SageMaker, Bedrock, RAG, agentic AI, and leading ML frameworks. You will play a key role in ensuring that AI solutions are secure, explainable, compliant, and aligned with demanding enterprise and mission requirements. Accountabilities • Lead AI/ML strategy, solution architecture, technical implementation, and modernization initiatives across complex programs. • Design, develop, integrate, and deploy scalable AI/ML models and intelligent systems supporting decision-making, automation, productivity, and operational readiness. • Lead the development of predictive analytics capabilities, automation frameworks, and intelligent decision-support solutions. • Provide hands-on technical leadership throughout the AI/ML development lifecycle, from experimentation and prototyping through production deployment and ongoing optimization. • Oversee data engineering pipelines, MLOps processes, model lifecycle management, validation, monitoring, explainability, and bias mitigation. • Integrate AI/ML capabilities into secure enterprise and restricted environments while incorporating cybersecurity, data governance, ethical AI, and compliance requirements into development workflows. • Support security risk management activities, including threat assessments, authorization documentation, configuration management, incident response documentation, audits, and governance reviews. • Ensure AI/ML solutions align with applicable risk management and cybersecurity frameworks and maintain continuous compliance. • Collaborate with security teams, business owners, technical stakeholders, and program leadership to deliver secure and effective AI solutions. • Advise leadership on emerging AI technologies, practical mission applications, modernization opportunities, and responsible AI practices. • Help transition experimental and prototype AI capabilities into reliable, scalable production systems. • Mentor junior engineers and provide technical guidance across multidisciplinary teams. Requirements • Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical discipline; a Master’s degree or PhD is preferred. • 10+ years of progressive experience in AI/ML, data science, software engineering, advanced analytics, or a closely related field, including substantial hands-on experience with modern AI technologies. • At least 5 years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments, including experience with MLOps practices. • Demonstrated ability to personally develop AI/ML solutions rather than focusing exclusively on architecture or management. • Strong programming skills in Python, R, Java, or comparable languages. • Deep knowledge of machine learning frameworks such as TensorFlow or PyTorch, ideally with implementation experience using AWS SageMaker. • Experience integrating AI/ML solutions into secure enterprise environments and working within cybersecurity, data governance, regulatory, and compliance requirements. • Practical experience building AI products or functional prototypes using Retrieval-Augmented Generation (RAG) and agentic AI technologies. • Experience with cloud platforms, preferably AWS, with Azure or Google Cloud experience also considered. • Familiarity with AI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI. • Experience implementing AI solutions in secure, restricted, regulated, or highly governed environments. • Ability to obtain Public Trust clearance and meet applicable background eligibility requirements. • Must have lived in the United States for at least 3 of the last 5 years. • Experience with enterprise-scale Salesforce solutions is preferred, particularly Agentforce implementations. • Familiarity with AI governance, responsible AI, modernization programs, and enterprise transformation initiatives is advantageous. • Experience supporting U.S. federal agencies, particularly healthcare or public-sector organizations, is preferred. • Experience with AWS GovCloud, Azure Government, Zero Trust architectures, or comparable secure-cloud environments is a strong advantage. • Strong communication, stakeholder management, problem-solving, mentoring, and technical leadership skills. Benefits • Estimated salary range of $204,000–$276,000, with actual compensation determined by experience, geographic location, and applicable contractual considerations. • Comprehensive medical plan options, including plans with Health Savings Accounts. • Dental and vision insurance options. • 401(k) plan with company matching and pre-tax and post-tax contribution options. • Paid time off, including vacation, sick, personal, holiday, parental, military, bereavement, and jury-duty leave. • Typically 15 days of paid leave per calendar year for vacation, personal business, and illness, plus 10 paid holidays. • Paid family leave of up to 160 hours within a rolling 12-month period for eligible employees. • Short- and long-term disability coverage, life insurance, accidental death and dismemberment coverage, and other insurance options. • Flexible work arrangements designed to support work-life balance. • Career development resources, including AI-powered career planning and learning opportunities. • Internal mobility support to help employees pursue long-term career goals. • Opportunities to work with advanced AI, cloud, cybersecurity, and software technologies on complex, high-impact initiatives. • Collaborative environment with opportunities to mentor others and influence technical strategy. • Full-time schedule of 40 hours per week, with limited travel of less than 10%. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevan

Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical discipline; a Master’s degree or PhD is preferred. 10+ years of progressive experience in AI/ML, data science, software engineering, advanced analytics, or a closely related field, including substantial hands-on experience with modern AI technologies. At least 5 years of hands-on experience designing, developing, and deploying AI/ML solutions in production environments, including experience with MLOps practices. Demonstrated ability to personally develop AI/ML solutions rather than focusing exclusively on architecture or management. Strong programming skills in Python, R, Java, or comparable languages. Deep knowledge of machine learning frameworks such as TensorFlow or PyTorch, ideally with implementation experience using AWS SageMaker. Experience integrating AI/ML solutions into secure enterprise environments and working within cybersecurity, data governance, regulatory, and compliance requirements. Practical experience building AI products or functional prototypes using Retrieval-Augmented Generation (RAG) and agentic AI technologies. Experience with cloud platforms, preferably AWS, with Azure or Google Cloud experience also considered. Familiarity with AI services such as AWS Bedrock, Azure AI Foundry, or Google Vertex AI. Experience implementing AI solutions in secure, restricted, regulated, or highly governed environments. Ability to obtain Public Trust clearance and meet applicable background eligibility requirements. Must have lived in the United States for at least 3 of the last 5 years. Experience with enterprise-scale Salesforce solutions is preferred, particularly Agentforce implementations. Familiarity with AI governance, responsible AI, modernization programs, and enterprise transformation initiatives is advantageous. Experience supporting U.S. federal agencies, particularly healthcare or public-sector organizations, is preferred. Experience with AWS GovCloud, Azure Government, Zero Trust architectures, or comparable secure-cloud environments is a strong advantage. Strong communication, stakeholder management, problem-solving, mentoring, and technical leadership skills.

Lead AI/ML strategy, solution architecture, technical implementation, and modernization initiatives across complex programs. Design, develop, integrate, and deploy scalable AI/ML models and intelligent systems supporting decision-making, automation, productivity, and operational readiness. Lead the development of predictive analytics capabilities, automation frameworks, and intelligent decision-support solutions. Provide hands-on technical leadership throughout the AI/ML development lifecycle, from experimentation and prototyping through production deployment and ongoing optimization. Oversee data engineering pipelines, MLOps processes, model lifecycle management, validation, monitoring, explainability, and bias mitigation. Integrate AI/ML capabilities into secure enterprise and restricted environments while incorporating cybersecurity, data governance, ethical AI, and compliance requirements into development workflows. Support security risk management activities, including threat assessments, authorization documentation, configuration management, incident response documentation, audits, and governance reviews. Ensure AI/ML solutions align with applicable risk management and cybersecurity frameworks and maintain continuous compliance. Collaborate with security teams, business owners, technical stakeholders, and program leadership to deliver secure and effective AI solutions. Advise leadership on emerging AI technologies, practical mission applications, modernization opportunities, and responsible AI practices. Help transition experimental and prototype AI capabilities into reliable, scalable production systems. Mentor junior engineers and provide technical guidance across multidisciplinary teams.