Build the future of AI at enterprise scale

Are you passionate about Generative AI, large-scale data platforms, and cloud-native architecture? Do you want to design AI solutions that move beyond experimentation and into real-world, business-critical impact?

We are looking for a senior AI & Data Solutions Architect to lead the design and delivery of next-generation AI, GenAI, and data-driven platforms within a complex enterprise environment. This role sits at the intersection of AI innovation, cloud architecture, and business transformation, with exposure to telecom environments and cutting-edge GPU-powered AI workloads.

Requirements

What You’ll Be Doing

As an AI & Data Solutions Architect, you will:

• Architect and deliver end-to-end AI and GenAI solutions aligned to strategic business objectives
  

• Design scalable AI and data platforms across Azure, AWS, and/or GCP
  

• Build and refine LLM-based applications, including advanced prompt engineering
  

• Develop, train, deploy, and operate AI/ML models using modern MLOps practices
  

• Integrate AI solutions with cloud-native AI services, LLM platforms, and enterprise systems
  

• Leverage platforms such as Azure Machine Learning for model lifecycle management
  

• Design and support GPU-powered AI workloads, including NVIDIA H-series architectures
  

• Ensure ethical, responsible, and compliant AI across all implementations
  

• Stay ahead of the curve on Generative AI, LLMs, and AI infrastructure trends
  

• Collaborate closely with business leaders, data engineers, IT teams, and external partners
  

What We’re Looking For

Must-Have Skills & Experience

• Strong understanding of AI/ML concepts and solution architectures
  

• Advanced Python proficiency
  

• Hands-on experience with GenAI, LLM-based applications, and prompt engineering
  

• Solid understanding of MLOps pipelines and model lifecycle management
  

• Exposure to NVIDIA H200 / GPU-based AI workloads
  

• Experience working within or alongside telecom environments
  

• Deep, hands-on experience with Azure, AWS, and/or GCP
  

• Strong knowledge of cloud-based data storage and processing platforms
  

Nice-to-Have (Bonus)

• Kubernetes and Docker
  

• Azure DevOps
  

• Azure Cosmos DB
  

• Java and/or Ruby on Rails
  

• Experience managing large-scale, GPU-intensive AI platforms
  

Screening Questions:

·       Describe your experience designing and deploying GenAI or LLM-based solutions.

·       What is your hands-on experience with MLOps pipelines in a cloud environment?

·       Which cloud platforms (Azure/AWS/GCP) have you architected AI solutions on, and at what scale?

·       Have you worked with GPU-based AI workloads (e.g., NVIDIA H-series)? Please explain.

·       What exposure do you have to telecom data or systems, if any?

Benefits

Why Join?

• Architect enterprise-scale AI solutions, not just proofs of concept
  

• Work with cutting-edge GenAI and GPU technology
  

• Influence strategy, architecture, and standards across a large organisation
  

• Collaborate with senior stakeholders on high-impact AI transformation initiatives
  

• Be part of a team shaping the future of AI adoption in telecom and enterprise environments