Primary Purpose of the Job:
The Senior Digital Architect is responsible for designing, implementing, and maintaining Cloud digital platforms across the organization. This role focuses on enhancing enterprise analytics capabilities by integrating AI/ML models, emerging technologies, and large-scale data processing frameworks to drive data-driven decision-making and operational efficiency. Additionally, the digital architect will collaborate with business and technical teams to accelerate digital transformation, streamline data governance, and adopt emerging technologies to drive continuous innovation.
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Design scalable, secure, and cloud-native architecture frameworks for AI/ML solutions, including MLOps pipelines, model deployment infrastructure, and integration patterns.
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Establish architectural guidelines for implementing generative AI solutions, including safety measures and ethical considerations.
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Design scalable architectures for packaging AI/ML models as production-ready APIs or custom applications/microservices.
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Define technical standards for model deployment, monitoring, and maintenance.
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Identify and evaluate industry-specific data and AI platforms, Auto-ML tools to fit business use cases and derive value.
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Partner with business stakeholders to understand requirements and translate them into technical solutions
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Establish governance frameworks for AI model lifecycle management
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Assess technical and Information security risks and provide mitigation strategies in the implementation of digital solutions
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Audit AI tools and practices across data, models and engineering, focusing on continuous improvement and feedback mechanisms.
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Provide strategic and technical guidance to stakeholders regarding digital solutions, cloud architecture, and platform optimizations.
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Stay updated on emerging technologies and apply cloud-native, AI/ML-driven solutions, automation tools to foster innovation in business processes.
Required Experience and Skills:
AI/ML Expertise
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8+ years of experience in digital solution architecture, with at least 5 years focusing on AI/ML solutions preferably in the Energy Sector.
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Proven track record of designing and implementing enterprise-scale AI/ML architecture/solutions.
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5+ years of experience with AI/ML frameworks (TensorFlow, PyTorch, etc.) and AI model deployment.
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Proficient in large language models and generative AI implementations.
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Experience in prompt engineering, RAG, and fine-tuning to optimize model performance and response accuracy.
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Experienced with real-time ML systems and edge computing.
MLOps and DataOps
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Strong knowledge of MLOps practices and tools.
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Proficiency in MLOps and DataOps methodologies, including CI/CD pipelines, ML model monitoring, and automation.
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Experience with DevOps, serverless computing, and containerization (Docker, OpenShift, Kubernetes).
Cloud and Architecture
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Strong expertise in one of the cloud computing platforms (Azure, GCP), cloud services (SaaS, PaaS, DaaS), and microservices-driven architectures.
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Experience in designing scalable architectures for packaging AI/ML models as production-ready APIs or custom applications/microservices.
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Working knowledge of system integration approaches, modern data architectures, and cloud-native application design.
Governance and Compliance
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In-depth understanding of data governance frameworks, cybersecurity principles, regulatory compliance, and AI ethics in enterprise settings.
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Knowledgeable in AI/ML regulatory compliance.
Communication and Collaboration
Excellent communication skills to effectively collaborate with business, technical, and product teams and translate complex technical requirements into actionable solutions
Educational Qualifications:
- A degree in Information Management, Engineering, or a technology related field, demonstrating strong analytical and quantitative skills.
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Advanced degrees (Master's or PhD) in Data Science, Applied Machine Learning, Computer Science, or Statistics is highly desirable