Senior Digital Architect

About the Role

The Senior Digital Architect will lead the design, development, and maintenance of cloud-based digital platforms at the enterprise level, focusing especially on embedding AI and ML technologies to improve analytics and operational effectiveness. This role requires partnering with both business and technical teams to expedite digital transformation initiatives, enhance data governance, and leverage emerging technologies for sustainable innovation.

Key Responsibilities

• Create scalable, secure, and cloud-native architectural frameworks tailored for AI/ML solutions, including pipelines for MLOps, infrastructure for model deployment, and integration patterns.
• Develop architectural standards for generative AI implementations, incorporating safety protocols and ethical guidelines.
• Design infrastructures that enable packaging AI/ML models into production-ready APIs or microservices applications.
• Define technical criteria for deployment, monitoring, and upkeep of AI models in production environments.
• Evaluate and select industry-specific data platforms, AI tools, and AutoML solutions aligned with business needs.
• Collaborate with stakeholders to gather requirements and convert them into robust technical architectures.
• Implement governance structures to manage the AI model lifecycle effectively.
• Identify security risks related to digital solutions and devise appropriate mitigation strategies.
• Regularly audit AI tools, data integrity, models, and engineering practices to promote continuous improvements.
• Offer strategic advice and technical assistance on cloud architectures and platform enhancements related to digital solutions.
• Keep abreast of emerging technologies to integrate cloud-native, AI-driven, and automation tools that advance business processes.

Required Skills and Experience

• Over 8 years in digital solution architecture with a minimum of 5 years dedicated to AI/ML-focused architectures, preferably in the energy industry.
• Documented success in delivering large-scale AI/ML enterprise solutions.
• At least 5 years' experience working with AI/ML frameworks such as TensorFlow and PyTorch along with hands-on AI model deployment experience.
• Expertise in large language models and generative AI applications.
• Proficiency in prompt engineering, retrieval-augmented generation (RAG), and fine-tuning AI models for enhanced performance.
• Experience with real-time machine learning systems and edge computing technologies.
• Strong command over MLOps and DataOps including CI/CD pipelines, model monitoring, and process automations.
• Experience with DevOps practices, containerization using Docker, OpenShift, Kubernetes, and serverless computing.
• Advanced knowledge of cloud platforms like Azure or Google Cloud Platform, SaaS/PaaS/DaaS services, and microservices architecture.
• Familiarity with modern data architectures, cloud-native design, and system integration methods.
• Deep understanding of data governance, cybersecurity, compliance requirements, and ethical considerations related to AI/ML.
• Excellent communication skills enabling collaboration with product, technical, and business teams to deliver actionable solutions.
• A degree in Information Management, Engineering, or related technology fields. Advanced qualifications such as Master's or PhD in Data Science, Applied Machine Learning, Computer Science, or Statistics are highly favored.