Cloud-Native Architect

3 days ago


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

What We Offer:

As a Senior Digital Architect at Qatar Petroleum International Ltd., you will have the opportunity to work on exciting projects, collaborating with cross-functional teams to drive innovation and growth.

Responsibilities:

  • Designing and implementing cloud digital platforms across the organization.
  • Establishing architectural guidelines for AI/ML solutions, ensuring safety measures and ethical considerations.
  • Developing technical standards for model deployment, monitoring, and maintenance.
  • Identifying and evaluating industry-specific data and AI platforms, Auto-ML tools to fit business use cases and derive value.
  • Collaborating with business stakeholders to understand requirements and translate them into technical solutions.
  • Establishing governance frameworks for AI model lifecycle management.
  • Assessing technical and information security risks and providing mitigation strategies in the implementation of digital solutions.

Requirements:

  • 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.

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.

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.

Governance and Compliance:

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

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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