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AI Solutions Architect

AI Solutions Architect

Eames Consulting Group
8-10 Years
Early Applicant
  • Posted 3 days ago
  • Be among the first 10 applicants

Job Description

We are partnered with an established global financial institution looking to expand their enterprise technology capabilities across the region.

They are seeking a seasoned Solution Architect spearhead the design and integration of their core enterprise AI platform. In this role, you will be the bridge between strategic business objectives and enterprise-grade AI deployment, ensuring architectures are production-ready, highly secure, and optimised for scale.

Key Responsibilities:

  • Architect and lead the end-to-end blueprint for an enterprise level AI platform, covering data pipelines, deployment infrastructure, and live model lifecycle management.
  • Convert complex institutional use cases into modular, scalable technical roadmaps and microservices architectures.
  • Partner with cross-functional engineering teams, data science units, and executive stakeholders to drive the execution of modern machine learning and generative AI solutions.
  • Define and enforce governance frameworks, data privacy boundaries, and enterprise security guardrails across all deployed AI systems.
  • Ensure all deployed architectures adhere strictly to high-availability, scalability, and regulated platform performance standards.

Requirements:

  • At least 8 years of experience in software engineering, data architecture, and distributed systems, with 5+ years dedicated specifically to production AI/ML solution design.
  • Strong architectural proficiency across major cloud environments (AWS, Azure, or GCP) utilizing modern microservices and API-first designs.
  • Hands-on familiarity with core programming environments (Python, Java, or Scala), data engineering frameworks, and generative AI/LLM deployment patterns.
  • Deep knowledge of secure SDLC, model monitoring, and regulatory compliance standards within heavily governed domains (e.g., Banking, Financial Services, Healthcare).
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Engineering, or a related technical discipline.

More Info

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Industry:
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Key Skills

deployment infrastructure

data pipelines

generative AI solutions

microservices architectures

live model lifecycle management

data engineering frameworks

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