Role Description We are seeking an innovative and skilled AI Developer to design, build, and deploy artificial intelligence and machine learning solutions. This role requires a strong foundational expertise in AI development with the capacity to take on high-level technical challenges and guide project architecture. You will be instrumental in bridging the gap between raw data and intelligent, automated product features, working closely with our engineering and product teams to bring AI concepts into production. - Model Development: Design, train, and implement machine learning models and AI algorithms tailored to specific business needs. - Data Engineering: Assist in building and optimizing data pipelines, ensuring that data gathering, cleaning, and preprocessing are handled efficiently. - API Integration: Integrate both custom-built models and third-party AI APIs (such as Large Language Models) into existing software applications. - Deployment & Scaling: Deploy AI models into production environments, ensuring they are scalable, efficient, and reliable. - Testing & Optimization: Continuously monitor model performance, fine-tuning and retraining as necessary to maintain high accuracy and reduce bias. Qualifications - Experience: 3–5+ years of professional experience in software engineering, with a strong, proven focus on Artificial Intelligence and Machine Learning. - Programming Languages: Familiarity with other languages like Python, C++, Java, or JavaScript is a plus. - AI/ML Frameworks: Experience with industry-standard machine learning libraries and frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, Keras). - Cloud & MLOps: Familiarity with deploying models on cloud platforms (AWS, Google Cloud, or Azure) and understanding of MLOps best practices. - Analytical Skills: Strong foundation in mathematics, statistics, and complex algorithms. - Autonomy: Highly self-motivated with the ability to take a project from conceptualization to deployment, comfortably bridging mid-level execution and senior-level architectural decisions. Requirements - Employment Type: Full Time - Location: Remote - Working Hours: US Business Hours Benefits - Performance-based raises - Minimum 5 days of time off annually - Annual cost-of-living-adjustments at one-year anniversary

• Du unterstützt bei der Entwicklung produktiver AI-Use-Cases – von der Idee über den Prototypen bis zur Produktivsetzung. • Du entwickelst, testest und dokumentierst Prompts, Workflows und Automatisierungen mit modernen AI-Tools. • Du unterstützt bei der Entwicklung und Durchführung von Schulungen, Workshops und Trainings rund um AI. • Du erstellst praxisnahe Lernmaterialien, Prompt-Sammlungen und Use-Case-Bibliotheken. • Du hilfst dabei, den Erfolg unserer Use Cases anhand relevanter Kennzahlen messbar zu machen.

Role Description The Global Consolidated Customer Data & AI Lead is a strategic leadership role with a dual mandate: globally, shaping consolidated customer data as a critical enterprise asset, and locally, translating Data & AI strategy into scalable business impact across multiple priority markets, with the U.S. and Canada as core markets. This role is central to building a more connected, trusted, and insight-led commercial engine. The successful candidate will turn harmonized customer data from various sources into competitive advantage by enabling: - Analytics - AI - Omnichannel engagement - Customer segmentation - Decision-making at global scale By combining global domain ownership with multi-market execution, this role bridges strategy and delivery. It ensures that enterprise standards, data products, and governance frameworks are shaped by real market needs. As AI becomes a core operating layer for commercial decision-making, customer data is evolving into continuous commercial intelligence. This role will help shape that future by: - Strengthening data foundations - Improving governance - Resolving duplication - Enabling intelligent systems for faster insight generation - More personalized engagement - Better investment decisions - Scalable growth across markets, channels, and customer types Qualifications - Master’s degree in Business, Economics, Data Science, Information Management, or a related field, or a bachelor’s degree with equivalent experience. - Proven experience as a Business Data Domain Owner with end-to-end accountability for domain strategy, governance, quality, priorities, and business alignment, ideally in customer or account data. - Deep knowledge of customer data ecosystems, master data, retailer hierarchies, distributor records, identity resolution, matching and deduplication, and third-party enrichment sources. - Strong knowledge of data governance frameworks, master data management principles, and golden record logic. - Track record of enabling analytics and AI use cases through high-quality, well-structured, and compliant customer data. - AI-native mindset with strong curiosity, hands-on AI literacy and tool use. - Experience partnering with IT to integrate customer data into enterprise platforms. - Demonstrated success leading customer data consolidation or harmonization initiatives. - Proven experience working with IT teams on data strategy, governance, architecture, and compliance. - Strong knowledge of GDPR, US state privacy laws, and third-party data usage rights. - Experience with the Focus markets US and Canada commercial data landscape. - Strong leadership, communication, and stakeholder management skills. - Fluent English required; additional languages such as French or Spanish are an advantage. Requirements - Co-shaping in defining and executing the multiple markets with focus on US and Canada Data & AI strategy. - Translate global data domain strategies into effective execution in Focus markets US and Canada. - Support NA data governance, management, and quality for customer and procured data assets. - Collaborate with cross-functional stakeholders to translate data needs into actionable insights. - Work closely with IT to enable scalable, secure, and accessible data platforms. - Integrate process design, information architecture, data architecture, and user experience considerations. - Support cross-functional teams in Focus markets US and Canada by promoting a data-as-an-asset mindset. - Manage day-to-day Focus markets US and Canada data priorities. Benefits - Salary between $144160-216240. - Additional compensation may include a bonus or commission. - Health care, vision, dental, retirement, PTO, sick leave, etc.

Role Description As a premier banking institution in Egypt, we are rapidly scaling our cutting-edge AI and Machine Learning capabilities. To ensure this innovation does not compromise our security posture, our Cybersecurity Department is looking for an expert AI Cybersecurity Architect. In this highly strategic role, you will be the foundational architect behind the bank’s AI security governance. You will not just react to threats; you will build the comprehensive control frameworks, policies, and architectural standards that govern how AI models, Large Language Models (LLMs), and big data pipelines are safely developed, deployed, and managed across the enterprise. Key Responsibilities - Establish AI Security Governance Frameworks: Author, implement, and maintain the bank's enterprise-wide AI Security Policy. Align our internal AI governance with international standards (such as NIST AI RMF, ISO/IEC 42001, and OWASP Top 10 for LLMs) while strictly ensuring compliance with evolving Central Bank of Egypt (CBE) regulations and the Egyptian Data Protection Law. - Design & Build Cybersecurity Controls: Architect, enforce, and validate technical and administrative security controls tailored for the entire AI/ML lifecycle (Data Ingestion, Training, Deployment, and Inference). This includes building robust controls against data poisoning, model inversion, prompt injection, and unauthorized data exfiltration. - Secure MLOps Architecture: Define the reference architectures and secure guardrails for our Machine Learning Operations (MLOps) pipelines. Ensure that security checks, vulnerability scanning, and model integrity verifications are seamlessly integrated into our continuous deployment workflows. - Advanced AI Threat Modeling & Risk Assessment: Lead comprehensive risk assessments and threat-modeling exercises on all proprietary and third-party AI implementations. Identify structural risks in algorithmic logic, training data pipelines, and API integrations, translating technical risks into clear business governance metrics. - Third-Party & Vendor AI Governance: Develop and execute rigorous cybersecurity assessment frameworks for evaluating third-party AI tools, cloud-hosted models, and external vendors, ensuring they meet the bank’s strict data privacy and control standards. Qualifications - 8+ years of progressive experience in Cybersecurity Architecture or IT Risk Governance, with at least 3+ years of dedicated experience explicitly focused on securing AI/ML systems and building enterprise governance frameworks. - Minimum of 3 years of experience working within a regulated financial institution in Egypt. You must possess an intricate understanding of CBE cybersecurity circulars, auditing standards, and banking compliance requirements. - Proven track record of designing, writing, and implementing complex cybersecurity control frameworks from scratch. Deep familiarity with traditional frameworks (NIST SP 800-53, ISO 27001) as well as modern AI-specific guardrails is a must. - Strong conceptual and practical understanding of AI/ML infrastructure, including neural networks, LLM orchestration layers, vector databases, and cloud data platforms (Azure, AWS, or hybrid environments). You must speak the language of both data scientists and enterprise security engineers. - Bachelor’s degree in Cybersecurity, Computer Engineering, Computer Science, or a related technical discipline. - Elite security certifications are highly preferred (e.g., CISSP, CISM, CRISC, or CCSP), alongside any specialized AI security credentials. - Exceptional communication and stakeholder management skills. You must possess the professional maturity to present complex AI risks to C-suite executives and board members, while maintaining the technical credibility to influence data science teams. Fluency in English. Benefits - Attractive, market-leading salary package - Clear career advancement path with professional development opportunities