About this role
<p><strong>AI Architect | WFH | Dayshift</strong></p> <p> </p> <p><strong>Role Summary:</strong></p> <p><br>The <strong>AI Architect (Architect Level)</strong> is a senior technology leader responsible for designing and overseeing <strong>enterprise AI/ML and Generative AI solutions</strong> for a global client, delivered via <strong>Atos Global Delivery Center (GDC) Philippines</strong>. This role drives the AI strategy and architecture, ensuring solutions are scalable, secure, and aligned with both <strong>business objectives</strong> and <strong>industry best practices</strong>. 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 <strong>value in a managed services (AMS) context</strong>.</p> <p> </p> <p> </p> <p><strong>Key Responsibilities:</strong></p> <ul> <li style="list-style-type:disc"> <p><strong>AI Solution Design & Architecture:</strong> Design end-to-end <strong>AI/ML architectures</strong> (including <strong>Generative AI</strong> and traditional ML models) that address business needs and can scale across global operations.</p> </li> <li style="list-style-type:disc"> <p><strong>Integration & Deployment:</strong> Define and oversee integration of AI solutions into <strong>cloud environments</strong> (e.g., AWS, Azure, GCP) and existing enterprise platforms. Ensure <strong>MLOps/DevOps pipelines</strong> (CI/CD for ML models) are established for continuous delivery and automation of AI services.</p> </li> <li style="list-style-type:disc"> <p><strong>Technical Leadership:</strong> Provide <strong>technical leadership</strong> and guidance to data scientists, ML engineers, and software development teams. Review solution designs, code, and model performance to ensure best practices are followed.</p> </li> <li style="list-style-type:disc"> <p><strong>Enterprise Standards & Governance:</strong> Ensure AI solutions comply with <strong>enterprise architecture standards</strong>, security policies, data privacy regulations (e.g., <strong>GDPR</strong>), and <strong>governance</strong> requirements. Establish guidelines for model management, data handling, and versioning.</p> </li> <li style="list-style-type:disc"> <p><strong>Stakeholder Collaboration:</strong> Work closely with business stakeholders and client leadership to understand requirements, translate them into technical solutions, and present architectural recommendations. <strong>Communicate complex AI concepts</strong> in a clear manner for decision-makers.</p> </li> <li style="list-style-type:disc"> <p><strong>Innovation & Best Practices:</strong> Stay updated on emerging AI/ML technologies (e.g., <strong>large language models, deep learning</strong>, advanced analytics). Evaluate and introduce <strong>best-in-class tools</strong> and frameworks (e.g., <strong>TensorFlow, PyTorch, scikit-learn</strong>) and <strong>cloud AI services</strong> (e.g., AWS SageMaker, Azure ML) to continuously improve AI capabilities.</p> </li> <li style="list-style-type:disc"> <p><strong>Performance & Continuous Improvement:</strong> 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.</p> </li> <li style="list-style-type:disc"> <p><strong>Documentation:</strong> Develop and maintain comprehensive <strong>architecture documents</strong>, design diagrams, and operational playbooks for AI solutions to ensure clarity and continuity across the support and development teams.</p> </li> </ul> <p style="list-style-type:disc"> </p> <p style="list-style-type:disc"> </p> <p><strong>Required Skills & Qualifications:</strong></p> <ul> <li style="list-style-type:disc"> <p><strong>Proven Experience:</strong> 8-12+ years in <strong>software/technology</strong> roles with at least <strong>4+ years in AI/ML architecture</strong> or similar senior positions. Strong track record of delivering <strong>AI/ML solutions on an enterprise scale</strong>.</p> </li> <li style="list-style-type:disc"> <p><strong>AI/ML Technical Expertise:</strong> Deep knowledge of <strong>machine learning, deep learning, and Generative AI</strong> techniques. Hands-on experience with <strong>AI/ML frameworks and libraries</strong> (e.g., TensorFlow, Keras, PyTorch, scikit-learn). Proficiency in programming (Python required; R/Java/Scala as plus).</p> </li> <li style="list-style-type:disc"> <p><strong>Data & Cloud Proficiency:</strong> Experience with <strong>data engineering</strong> (big data pipelines, ETL) and <strong>cloud platforms</strong> (AWS, Azure, GCP) for AI workloads (e.g., containerization with Docker/Kubernetes, use of cloud-native AI services, data lakes). Familiar with <strong>MLOps tools</strong> (e.g., MLflow, Kubeflow) and model deployment strategies.</p> </li> <li style="list-style-type:disc"> <p><strong>Architectural Knowledge:</strong> Strong understanding of <strong>microservices, APIs</strong>, and integrative architectures. Ability to design systems that include <strong>real-time data streaming</strong>, <strong>APIs</strong>, and integration with enterprise platforms. Working knowledge of <strong>DevOps</strong> practices for infrastructure automation (CI/CD, Infrastructure-as-Code) as they apply to ML models and data pipelines.</p> </li> <li style="list-style-type:disc"> <p><strong>Enterprise Security & Compliance:</strong> Solid grasp of <strong>cybersecurity principles</strong>, data encryption, user access controls, and <strong>compliance standards</strong> (GDPR, PCI, etc.) in designing AI solutions.</p> </li> <li style="list-style-type:disc"> <p><strong>Education:</strong> Bachelor’s degree in computer science, Engineering, or related field (Master’s or PhD in AI/ML, Data Science or related domain <strong>preferred</strong>).</p> </li> </ul> <p style="list-style-type:disc"> </p> <p style="list-style-type:disc"> </p> <p><strong>Preferred Skills (Nice to Have):</strong></p> <ul> <li style="list-style-type:disc"> <p><strong>Industry Domain Knowledge:</strong> Familiarity with <strong>hospitality industry</strong> systems and data (e.g., customer experience, loyalty programs) to better align AI solutions with client’s domain.</p> </li> <li style="list-style-type:disc"> <p><strong>Automation & Platforms:</strong> Experience integrating AI with <strong>workflow/automation platforms</strong> (e.g., ServiceNow, RPA tools) to enhance business processes.</p> </li> <li style="list-style-type:disc"> <p><strong>Big Data & Analytics:</strong> Exposure to <strong>big data technologies</strong> (Hadoop, Spark) and advanced analytics (data mining, predictive modeling).</p> </li> <li style="list-style-type:disc"> <p><strong>Architecture Frameworks:</strong> Certification or experience with enterprise architecture frameworks (<strong>TOGAF</strong>, <strong>ITIL</strong> for service management) and methodologies.</p> </li> <li style="list-style-type:disc"> <p><strong>Multilingual or Multi-cultural Exposure:</strong> Experience working in <strong>global teams</strong> or multi-cultural environments, especially within an <strong>offshore/onshore delivery model</strong>.</p> </li> </ul> <p style="list-style-type:disc"> </p> <p style="list-style-type:disc"> </p> <p><strong>Experience Level:</strong><br>Architect-level role intended for <strong>senior professionals</strong>. Ideally <strong>10+ years</strong> of total IT experience, including substantial <strong>leadership in AI/ML projects</strong> and previous roles as <strong>Lead AI/ML Engineer or Solution Architect</strong>. Demonstrated experience in <strong>architecting complex AI solutions</strong> in an enterprise or consulting setting.</p> <p><strong>Certifications:</strong></p> <ul> <li style="list-style-type:disc"> <p><strong>Cloud Certifications:</strong> AWS Certified Solutions Architect, Azure Solutions Architect Expert, Google Cloud Professional Architect or equivalent (<strong>strongly preferred</strong>).</p> </li> <li style="list-style-type:disc"> <p><strong>AI/ML Certifications:</strong> Certifications in AI/ML (e.g., <strong>Azure AI Engineer</strong>, <strong>Google Professional ML Engineer</strong>, <strong>IBM AI Enterprise Workflow</strong>) or <strong>Data Science</strong> credentials are advantageous.</p> </li> <li style="list-style-type:disc"> <p><strong>Architecture & Process:</strong> TOGAF (Enterprise Architecture) or ITIL (IT Service Management) certification <strong>a plus</strong>.</p> </li> </ul> <p style="list-style-type:disc"> </p> <p><strong>Soft Skills / Behavioral Expectations:</strong></p> <ul> <li style="list-style-type:disc"> <p><strong>Leadership & Communication:</strong> Excellent <strong>communication skills</strong> with ability to articulate technical concepts to non-technical stakeholders. Proven experience in <strong>leading technical teams</strong> and influencing decision-making in a cross-functional context.</p> </li> <li style="list-style-type:disc"> <p><strong>Problem-Solving:</strong> Strong analytical and <strong>problem-solving abilities</strong>, with a strategic mindset for addressing complex business challenges with AI solutions.</p> </li> <li style="list-style-type:disc"> <p><strong>Collaboration:</strong> Team player who excels in <strong>collaborative environments</strong>. Able to work effectively with remote, global teams (across different time zones) and build strong relationships with client stakeholders.</p> </li> <li style="list-style-type:disc"> <p><strong>Adaptability & Learning:</strong> High adaptability to rapidly evolving AI technologies. <strong>Continuous learner</strong> who keeps abreast of emerging trends and proactively upskills.</p> </li> <li style="list-style-type:disc"> <p><strong>Ethical Mindset:</strong> Strong sense of <strong>responsibility and ethics</strong> in AI, ensuring solutions are used responsibly and biases are managed.</p> </li> </ul> <p style="list-style-type:disc"> </p> <p><strong>Working Conditions:</strong></p> <ul> <li style="list-style-type:disc"> <p><strong>Offshore Delivery (Philippines):</strong> Based in Atos GDC Philippines, working <strong>remotely</strong> or from Atos offices, to deliver services for global operations.</p> </li> <li style="list-style-type:disc"> <p><strong>Global Collaboration:</strong> Must be flexible to collaborate with <strong>international teams</strong> (Europe, Asia, etc.), which may require adjusting work hours for occasional meetings across time zones.</p> </li> <li style="list-style-type:disc"> <p><strong>Managed Services Environment:</strong> Operates within a structured <strong>Application Management Services (AMS)</strong> and <strong>ITIL-driven support</strong> model, ensuring reliability and meeting service level agreements (SLAs).</p> </li> <li style="list-style-type:disc"> <p><strong>Travel:</strong> Minimal travel; primarily remote collaboration. Occasional on-site visits or travel for key client workshops may be required (as conditions allow).</p> </li> <li style="list-style-type:disc"> <p><strong>Work Hours:</strong> Standard business hours with flexibility. Willingness to provide <strong>leadership support during critical project phases or escalations</strong>, possibly outside normal hours if necessary.</p> </li> </ul> <p>#LI-PH <br>#LI-PHI<br>#LI-PHE<br> </p>