Digital Solutions Architect

4 days ago

Doha, Baladīyat ad Dawḩah, Qatar Qatar Petroleum International Ltd. Full time

Job Overview:

The role of a Senior Digital Architect at Qatar Petroleum International Ltd. is to design, implement, and maintain cloud digital platforms across the organization.

Key Responsibilities:

  • Design scalable architectures for AI/ML solutions, including MLOps pipelines, model deployment infrastructure, and integration patterns.
  • Establish architectural guidelines for implementing generative AI solutions, ensuring safety measures and ethical considerations.
  • Develop technical standards for model deployment, monitoring, and maintenance.
  • Identify and evaluate industry-specific data and AI platforms, Auto-ML tools to fit business use cases and derive value.
  • Collaborate with business stakeholders to understand requirements and translate them into technical solutions.
  • Establish governance frameworks for AI model lifecycle management.
  • Assess technical and information security risks and provide mitigation strategies in the implementation of digital solutions.
  • Audit AI tools and practices across data, models, and engineering, focusing on continuous improvement and feedback mechanisms.

Required Skills and Qualifications:

  • 8+ years of experience in digital solution architecture, with at least 5 years focusing on AI/ML solutions preferably in the Energy Sector.
  • Proven track record of designing and implementing enterprise-scale AI/ML architecture/solutions.
  • 5+ years of experience with AI/ML frameworks (TensorFlow, PyTorch, etc.) and AI model deployment.
  • Proficient in large language models and generative AI implementations.
  • Experience in prompt engineering, RAG, and fine-tuning to optimize model performance and response accuracy.
  • Experienced with real-time ML systems and edge computing.

MLOps and DataOps:

  • Strong knowledge of MLOps practices and tools.
  • Proficiency in MLOps and DataOps methodologies, including CI/CD pipelines, ML model monitoring, and automation.
  • Experience with DevOps, serverless computing, and containerization (Docker, OpenShift, Kubernetes).

Cloud and Architecture:

  • Strong expertise in one of the cloud computing platforms (Azure, GCP), cloud services (SaaS, PaaS, DaaS), and microservices-driven architectures.
  • Experience in designing scalable architectures for packaging AI/ML models as production-ready APIs or custom applications/microservices.
  • Working knowledge of system integration approaches, modern data architectures, and cloud-native application design.

Governance and Compliance:

  • In-depth understanding of data governance frameworks, cybersecurity principles, regulatory compliance, and AI ethics in enterprise settings.
  • 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.

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