AI Platform Architect

83zero; Greater London; On-site; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Bonus

Job summary

83zero in London is seeking an AI Platform Architect to lead design and delivery of enterprise-scale AI solutions in a hybrid setup (London - 1-2 days onsite). The role focuses on secure, production-ready AI platforms for a major financial services client within a global technology consultancy.

You will architect end-to-end AI/ML systems, define cloud-native solutions on GCP, and drive MLOps, LLMOps and AgentOps while ensuring governance, security and regulatory compliance across banking

Qualifications

• Proven experience delivering enterprise AI solutions as an AI/ML architect.
• Hands-on with GCP and cloud-native AI services.
• Strong governance, risk, and responsible AI practices.

Responsibilities

• Design end-to-end AI and ML architectures from data intake to deployment and monitoring.
• Define scalable cloud-native AI solutions on Google Cloud Platform.
• Lead architecture of enterprise AI platforms for traditional ML and Generative AI use cases.
• Drive MLOps, LLMOps, and AgentOps with CI/CD, registries, feature stores, and observability.
• Create secure, real-time, batch, and streaming AI inference solutions.
• Ensure governance, security and regulatory compliance for financial services.
• Collaborate with engineering, data, security and business teams to deliver production-ready AI capabilities.
• Provide technical leadership across multiple workstreams.

Skills

AI Architecture

GCP

MLOps

Security & Governance

Stakeholder Management

Regulated industries

Tools

Kubernetes

Docker

Terraform

CI/CD tooling

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.