AI Platform Architect
Job Description
AI Platform Architect
Location: London (Hybrid - 1-2 days per week)
Salary: £80,000 - £100,000 + Bonus & Excellent Benefits
We're partnering with a global technology consultancy delivering one of the UK's largest AI transformation programmes within the banking sector.
As an AI Architect , you'll play a key role in designing and delivering enterprise-scale AI solutions for a major financial services client. Working across architecture, engineering, and business teams, you'll define AI strategy, design scalable cloud-native solutions, and ensure AI platforms are secure, governed, and ready for production.
What You'll Be Doing
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Design end-to-end AI and Machine Learning architectures, from data ingestion through to model deployment and monitoring.
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Define scalable cloud-native AI solutions using Google Cloud Platform (GCP).
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Lead the architecture of enterprise AI platforms supporting both traditional Machine Learning and Generative AI use cases.
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Drive best practices across MLOps, LLMOps and AgentOps, including CI/CD, model registries, feature stores, lineage tracking and observability.
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Design secure, resilient real-time, batch and streaming AI inference solutions.
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Ensure AI solutions meet governance, security, regulatory and compliance requirements within financial services.
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Collaborate with engineering, data, security and business teams to deliver production-ready AI capabilities.
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Provide technical leadership and architectural guidance across multiple workstreams.
What We're Looking For
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Proven experience as an AI Architect, Enterprise Architect or Machine Learning Architect delivering enterprise AI solutions.
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Strong experience designing end-to-end AI/ML platforms and production-ready architectures.
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Hands-on knowledge of Google Cloud Platform (GCP) and cloud-native AI services.
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Experience with MLOps, LLMOps or AI platform engineering, including model lifecycle management and deployment pipelines.
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Strong understanding of AI governance, model risk, auditability and responsible AI practices.
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Experience working within regulated industries, ideally banking or financial services.
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Knowledge of cloud security, IAM, networking and secure architecture principles.
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Excellent stakeholder management skills with the ability to engage both technical and business audiences.
Desirable Experience
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Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI Agents.
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Kubernetes, Docker, Terraform or Infrastructure as Code.
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Experience delivering AI transformation programmes within enterprise organisations.
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