Senior Manager – AI Engineering (GenAI & MLOps Platform)

Discovered MENA United Kingdom
Relocation
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AI Summary

Lead the development of a Generative AI and MLOps platform, overseeing a team of engineers and contractors, and contributing to the scaling and evolution of enterprise AI platform capabilities.

Key Highlights
Lead the design and development of the organisation’s Generative AI and MLOps platform
Build and manage modern AI infrastructure
Collaborate with data scientists, AI engineers, and product teams
Key Responsibilities
Lead the design and development of the organisation’s Generative AI and MLOps platform
Build and manage modern AI infrastructure
Develop and maintain platform capabilities for GenAI applications
Establish engineering best practices, tooling, and platform standards
Collaborate with data scientists, AI engineers, and product teams
Lead and mentor a team of engineers and contractors
Technical Skills Required
Kubernetes Docker CI/CD frameworks AWS Azure RAG architectures Model deployment Monitoring Governance Machine Learning Generative AI
Benefits & Perks
Relocation to Abu Dhabi, UAE
10+ years of experience in AI engineering, machine learning engineering, or data platform engineering roles

Job Description


Senior Manager – AI Engineering (GenAI & MLOps Platform)

**THIS ROLE REQUIRES RELOCATION TO ABU DHABI, UAE. PLEASE ONLY APPLY IF YOU ARE OPEN TO RELOCATING TO THE UAE**


Discover the Opportunity:

We’re partnering with a major Abu Dhabi-based financial services organisation that is investing substantial capital into its AI transformation, building a world-class AI Centre of Excellence (CoE) to accelerate the development and deployment of AI across the business.


As part of this ambitious programme, the organisation is hiring a Senior AI Engineering Manager to lead the development of its Generative AI and MLOps platform, enabling scalable AI solutions across the business.


This is a highly visible leadership role combining deep hands-on technical expertise with platform ownership and team leadership. You will play a central role in designing the infrastructure, frameworks, and best practices that power conversational AI, agentic AI systems, and enterprise-scale machine learning platforms.


Discover the Role:

As Senior AI Engineering Manager, you will lead the development of the organisation’s GenAI and MLOps platform, ensuring that AI solutions can be built, deployed, and operated at scale.

Working as part of a rapidly expanding AI CoE, you will oversee a team of engineers and contractors responsible for building the foundational platforms that support AI product development across multiple business lines.


This role requires a leader who is highly technical and hands-on, capable of guiding architecture decisions while also contributing directly to engineering and platform development.


Discover the Responsibilities:

  • Lead the design and development of the organisation’s Generative AI and MLOps platform, enabling scalable AI deployment across the business
  • Build and manage modern AI infrastructure, including Kubernetes environments, CI/CD pipelines, and infrastructure-as-code frameworks
  • Develop and maintain platform capabilities for GenAI applications, including RAG architectures, model deployment, monitoring, and governance
  • Establish engineering best practices, tooling, and platform standards to support AI engineers building and deploying AI solutions
  • Collaborate with data scientists, AI engineers, and product teams to support the delivery of conversational AI, chatbots, and agentic AI applications
  • Lead and mentor a team of engineers and contractors, ensuring strong technical direction and delivery quality across AI platform initiatives
  • Contribute to the scaling and evolution of enterprise AI platform capabilities as part of the wider AI transformation programme


Discover the Requirements:

  • 10+ years of experience in AI engineering, machine learning engineering, or data platform engineering roles
  • Strong hands-on experience building MLOps platforms and AI infrastructure using technologies such as Kubernetes, Docker, and CI/CD frameworks
  • Experience building and deploying Generative AI applications, including RAG architectures, conversational AI, or agentic workflows
  • Strong cloud experience with AWS or Azure, including infrastructure-as-code and scalable ML deployment environments
  • Proven experience leading technical teams while remaining hands-on with architecture and code
  • Strong understanding of ML lifecycle management, model deployment, monitoring, and governance
  • Excellent stakeholder management skills and the ability to operate in fast-paced, high-impact AI environments

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