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    AI Platform Architect

    Technology
    83zero Ltd
    London
    Permanent
    £80,000 - £100,000/year
    Hybrid

    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

    • Design end-to-end AI and Machine Learning architectures, from data ingestion through to model deployment and monitoring.

    • Define scalable cloud-native AI solutions using Google Cloud Platform (GCP).

    • Lead the architecture of enterprise AI platforms supporting both traditional Machine Learning and Generative AI use cases.

    • Drive best practices across MLOps, LLMOps and AgentOps, including CI/CD, model registries, feature stores, lineage tracking and observability.

    • Design secure, resilient real-time, batch and streaming AI inference solutions.

    • Ensure AI solutions meet governance, security, regulatory and compliance requirements within financial services.

    • Collaborate with engineering, data, security and business teams to deliver production-ready AI capabilities.

    • Provide technical leadership and architectural guidance across multiple workstreams.

    What We're Looking For

    • Proven experience as an AI Architect, Enterprise Architect or Machine Learning Architect delivering enterprise AI solutions.

    • Strong experience designing end-to-end AI/ML platforms and production-ready architectures.

    • Hands-on knowledge of Google Cloud Platform (GCP) and cloud-native AI services.

    • Experience with MLOps, LLMOps or AI platform engineering, including model lifecycle management and deployment pipelines.

    • Strong understanding of AI governance, model risk, auditability and responsible AI practices.

    • Experience working within regulated industries, ideally banking or financial services.

    • Knowledge of cloud security, IAM, networking and secure architecture principles.

    • Excellent stakeholder management skills with the ability to engage both technical and business audiences.

    Desirable Experience

    • Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI Agents.

    • Kubernetes, Docker, Terraform or Infrastructure as Code.

    • Experience delivering AI transformation programmes within enterprise organisations.

    Posted on August 12, 2026

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