AI Architect

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 Ironwood Digital 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. Required Skills & Qualifications: 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 ). Preferred Skills (Nice to Have): 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-cul