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.
RequirementsWhat 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?
BenefitsWhy 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
Desired Skills:
- Generative AI & Large Language Models
- AI/ML Solutions Architect
- Prompt Engineering
- Python
- MLOps
- Cloud Architecture
- GPU-Accelerated
Desired Qualification Level:
- Degree
About The Employer: