Solution Architect - Cloud and AI/ML Systems

About the role

As a Solution Architect, you will be liable for building and delivering end-to-end technical solutions that meet business requirements. You will collaborate closely with product owners, data engineers, ML specialists and other stakeholders to develop scalable architectures across cloud platforms such as GCP and AWS. Your role will involve defining system components, data models, AI/ML solution design and technology choices to ensure robust, efficient, and compliant solutions. You will play a critical part in guiding the technical direction and leading the implementation teams to achieve successful project outcomes.

You will join a collaborative team liable in building and delivering cutting-edge solution architectures across cloud and on-premises environments. Working closely with product owners, data engineers, ML specialists, and cross-functional stakeholders, you will play a key role in shaping scalable, efficient, and innovative technology solutions that meet business needs.

What you’ll be doing

• Architect and deliver large-scale data platforms on GCP and AWS, integrating structured and unstructured data sources for analytics and AI
• Lead the end-to-end solution architecture and design for complex projects, ensuring alignment with business requirements.
• Collaborate closely with product owners, business analysts, ,engineering and ML engineer teams to gather requirements and translate them into scalable technical solutions.
• Define and implement AI integration patterns (model APIs, streaming inference, batch scoring, etc.) that align with enterprise data strategies
• 10+ years of experience in developing architectural frameworks for cloud platforms such as GCP and AWS, including on-premises integration where applicable.
• Define data models, technology components, and system validations to aid low-latency and batch processing needs.
• Ensure solutions are in best practices in containerization, using technologies like Kubernetes and Docker.
• Establish best practices for data security, lineage, and governance, ensuring compliance with internal and regulatory standards
• Drive planning, migration, and implementation activities to aid port business goals.
• Provide technical leadership and guidance to engineering teams during development and deployment phases.
• Maintain compliance with organizational standards and regulatory requirements throughout the solution lifecycle

Essential Skills / Experience

• Hands on experience in solution architecture with exposure to AI/ML systems design and deployment, preferably with expertise in cloud platforms such as GCP and AWS.
• Strong knowledge of end-to-end solution Architect /design for data, including on-premises and cloud-based architectures.
• Experience integrating AI models into enterprise systems using APIs, microservices, or event-driven frameworks
• Experience with containerization technologies like Kubernetes and Docker.
• Ability to translate business requirements into technical solutions and data models.
• Excellent communication and stakeholder management skills to collaborate with product owners, data engineers, and cross-functional teams.
• Delivered capability in strategic planning, migration, and implementation within an Agile environment.
• Experience working with real-time and batch data processing architectures and technologies such as Kafka.
• Ability to work independently in a fast-paced environment and manage multiple priorities effectively.

Desirable Skills / Experience

• A minimum of 10 years’ experience in Data & Analytics project and a minimum of 5-8 years of experience of playing a role of Solution Architect.
• Experience in design scalable Data Solutions to deliver on the business outcomes.
• Familiarity with Data Governance Polices and compliance.
• Experience in Software engineering best practices such as code reviews, reviewing frameworks, maintainability and readability
• Strong experience with data engineering technologies.
• Experience navigating large, complex organisational structures and driving continuous improvement.