AI Architect WFH Dayshift

Role Summary

The AI Architect (Architect Level) is a senior technology leader responsible for designing and overseeing enterprise AI/ML and Generative AI solutions for a global client, delivered via Atos Global Delivery Center (GDC) Philippines. This role drives the AI strategy and architecture, ensuring solutions are scalable, secure, and aligned with both business objectives and industry best practices. The AI Architect will collaborate with cross-functional teams (data science, cloud, DevOps/MLOps, and business stakeholders) to integrate AI capabilities into enterprise systems, optimize operations, and deliver value in a managed services (AMS) context.

Key Responsibilities

• AI Solution Design & Architecture Design end-to-end AI/ML architectures (including Generative AI and traditional ML models) that address business needs and can scale across global operations.
• Integration & Deployment Define and oversee integration of AI solutions into cloud environments (e.g., AWS, Azure, GCP) and existing enterprise platforms. Ensure MLOps/DevOps pipelines (CI/CD for ML models) are established for continuous delivery and automation of AI services.
• Technical Leadership Provide technical leadership and guidance to data scientists, ML engineers, and software development teams. Review solution designs, code, and model performance to ensure best practices are followed.
• Enterprise Standards & Governance Ensure AI solutions comply with enterprise architecture standards, security policies, data privacy regulations (e.g., GDPR), and governance requirements. Establish guidelines for model management, data handling, and versioning.
• Stakeholder Collaboration Work closely with business stakeholders and client leadership to understand requirements, translate them into technical solutions, and present architectural recommendations. Communicate complex AI concepts in a clear manner for decision-makers.
• Innovation & Best Practices Stay updated on emerging AI/ML technologies (e.g., large language models, deep learning, advanced analytics). Evaluate and introduce best-in-class tools and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud AI services (e.g., AWS SageMaker, Azure ML) to continuously improve AI capabilities.
• Performance & Continuous Improvement Oversee AI system performance and reliability in production (AMS setting). Identify opportunities for optimization, cost-efficiency, and enhancements to AI models and data pipelines over time.
• Documentation Develop and maintain comprehensive architecture documents, design diagrams, and operational playbooks for AI solutions to ensure clarity and continuity across the support and development teams.
  
  
  

• Proven Experience 8-12+ years in software/technology roles with at least 4+ years in AI/ML architecture or similar senior positions. Strong track record of delivering AI/ML solutions on an enterprise scale.
• AI/ML Technical Expertise Deep knowledge of machine learning, deep learning, and Generative AI techniques. Hands-on experience with AI/ML frameworks and libraries (e.g., TensorFlow, Keras, PyTorch, scikit-learn). Proficiency in programming (Python required; R/Java/Scala as plus).
• Data & Cloud Proficiency Experience with data engineering (big data pipelines, ETL) and cloud platforms (AWS, Azure, GCP) for AI workloads (e.g., containerization with Docker/Kubernetes, use of cloud-native AI services, data lakes). Familiar with MLOps tools (e.g., MLflow, Kubeflow) and model deployment strategies.
• Architectural Knowledge Strong understanding of microservices, APIs, and integrative architectures. Ability to design systems that include real-time data streaming, APIs, and integration with enterprise platforms. Working knowledge of DevOps practices for infrastructure automation (CI/CD, Infrastructure-as-Code) as they apply to ML models and data pipelines.
• Enterprise Security & Compliance Solid grasp of cybersecurity principles, data encryption, user access controls, and compliance standards (GDPR, PCI, etc.) in designing AI solutions.
• Education Bachelor’s degree in computer science, Engineering, or related field (Master’s or PhD in AI/ML, Data Science or related domain preferred).
  
  
  

• Industry Domain Knowledge Familiarity with hospitality industry systems and data (e.g., customer experience, loyalty programs) to better align AI solutions with client’s domain.
• Automation & Platforms Experience integrating AI with workflow/automation platforms (e.g., ServiceNow, RPA tools) to enhance business processes.
• Big Data & Analytics Exposure to big data technologies (Hadoop, Spark) and advanced analytics (data mining, predictive modeling).
• Architecture Frameworks Certification or experience with enterprise architecture frameworks (TOGAF, ITIL for service management) and methodologies.
• Multilingual or Multi-cultural Exposure Experience working in global teams or multi-cultural environments, especially within an offshore/onshore delivery model.
  
  
  

• Cloud Certifications AWS Certified Solutions Architect, Azure Solutions Architect Expert, Google Cloud Professional Architect or equivalent (strongly preferred).
• AI/ML Certifications Certifications in AI/ML (e.g., Azure AI Engineer, Google Professional ML Engineer, IBM AI Enterprise Workflow) or Data Science credentials are advantageous.
• Architecture & Process TOGAF (Enterprise Architecture) or ITIL (IT Service Management) certification a plus.
  
  
  

• Leadership & Communication Excellent communication skills with ability to articulate technical concepts to non-technical stakeholders. Proven experience in leading technical teams and influencing decision-making in a cross-functional context.
• Problem-Solving Strong analytical and problem-solving abilities, with a strategic mindset for addressing complex business challenges with AI solutions.
• Collaboration Team player who excels in collaborative environments. Able to work effectively with remote, global teams (across different time zones) and build strong relationships with client stakeholders.
• Adaptability & Learning High adaptability to rapidly evolving AI technologies. Continuous learner who keeps abreast of emerging trends and proactively upskills.
• Ethical Mindset Strong sense of responsibility and ethics in AI, ensuring solutions are used responsibly and biases are managed.
  
  
  

• Offshore Delivery (Philippines) Based in Atos GDC Philippines, working remotely or from Atos offices, to deliver services for global operations.
• Global Collaboration Must be flexible to collaborate with international teams (Europe, Asia, etc.), which may require adjusting work hours for occasional meetings across time zones.
• Managed Services Environment Operates within a structured Application Management Services (AMS) and ITIL-driven support model, ensuring reliability and meeting service level agreements (SLAs).
• Travel Minimal travel; primarily remote collaboration. Occasional on-site visits or travel for key client workshops may be required (as conditions allow).
• Work Hours Standard business hours with flexibility. Willingness to provide leadership support during critical project phases or escalations, possibly outside normal hours if necessary.