We are seeking an experienced AI and Data Solution Architect to own end-to-end architecture for data and AI products and platforms across data integration, classical machine learning, Generative AI and Agentic AI. The role is focused on designing secure, scalable and production-ready solutions across on-premise and cloud environments, including GCP, AWS and Azure, from prototype through to implementation

Own the end-to-end reference architecture for AI and data platforms, including data integration, model serving and the full classical ML, Generative AI and Agentic AI stack. Define secure-by-design blueprints across networking, identity, data governance and compliance for cloud and on-premise environments. Deliver High-Level Designs and reusable solution patterns for Generative AI and Agentic AI solutions, including RAG, orchestration, guardrails and evaluation. Create implementation plans and MLOps or LLMOps approaches aligned to the roadmap, including risk assessment and cost-performance trade-off recommendations. Identify capability gaps across the AI and data landscape and recommend platform enablement paths to support scalable delivery.

Opportunity to shape end-to-end architecture for modern AI and data platforms across cloud and on-premise environments. Exposure to advanced AI domains, including classical machine learning, Generative AI and Agentic AI. Opportunity to influence secure, scalable architecture patterns across networking, identity, compliance, governance and cloud services. Scope to contribute reusable design patterns, High-Level Designs and platform enablement recommendations for AI and data delivery. Collaboration with international, distributed teams on complex, multi-disciplinary technology initiatives.

Advanced solution architecture for AI and data platforms spanning data integration, model serving, MLOps and LLMOps. Practical architecture approaches for Generative AI and Agentic AI, including RAG, orchestration, guardrails and evaluation Secure-by-design architecture practices across cloud and on-premise technology landscapes. Cost, performance and risk assessment techniques for scalable AI and data solution delivery. Broader exposure to cloud AI and data services across GCP, AWS and Azure.

Desired Candidate Profile

You have hands-on experience designing end-to-end AI and data solutions across classical machine learning, Generative AI and Agentic AI. You bring strong knowledge of secure-by-design principles, security, networking and compliance standards. You understand data integration, MLOps or LLMOps, and model-serving design patterns. You have solid knowledge of cloud AI and data services across GCP, AWS or Azure, as well as modern Generative AI tooling. You have a background in IT infrastructure, networking, identity and automation. You hold a bachelor s degree in Computer Science, Engineering or a related subject. You have 5+ years experience in a similar role architecting large-scale data and/or AI platforms. You have experience working in international, distributed teams and delivering projects across multi-disciplinary areas of differing size and complexity. Experience with data modelling, data governance, responsible AI principles, RAG or vector-search architectures, agentic frameworks, data streaming, batching, event-driven mechanisms, AI observability, evaluation and monitoring tool stacks would be beneficial. Experience with GenAI, LLM and data tooling such as vector databases, Kafka and cloud ML platforms would be beneficial.