AI Ops Platform Engineer – London Canary Wharf | Visa + Salary Insights

📍 Location: gb

🏷 Type: Not specified

Job Intelligence

📍 More in this location:
Browse AI jobs in gb

🏷 Similar roles:

🌐 Explore all jobs:
View all AI job listings

Job Overview

This role focuses on building and scaling a production-grade AI Ops platform within a global financial services environment, supporting merchant payments, fraud detection, and AI-driven decision systems. The ideal candidate is a Senior-Level (5+ years) engineer with deep expertise in MLOps, LLMOps, and cloud-native AI systems. You will lead engineering squads, shape AI infrastructure strategy, and ensure enterprise-grade governance, reliability, and scalability. This position is designed for professionals who can balance hands-on engineering with architectural leadership in regulated, high-impact environments such as banking and payments systems.

🌍 Work Eligibility & Location

This is a London-based engineering leadership position with strong alignment to UK financial systems. While full remote work is not indicated, hybrid flexibility may apply depending on team structure. International candidates may require visa sponsorship evaluation depending on experience and business need.

💰 Salary Intelligence

Given the VP-level expectations and deep technical ownership across AI platforms, this role sits in a premium compensation band. The £95K–£160K+ range reflects London fintech standards for senior AI infrastructure engineers with leadership responsibilities. Compensation is likely supplemented with performance bonuses and long-term incentives.

📊 Role Breakdown

This role is centered on designing and operating an enterprise-grade AI Ops platform that powers Generative AI and Machine Learning systems at scale. You will lead end-to-end lifecycle management of AI systems, including model deployment, prompt orchestration, monitoring, governance, and cost optimization. A key focus is building robust pipelines for LLMOps and MLOps using AWS-native tools and secure engineering patterns.

You will work extensively with AWS Bedrock, Lambda, Step Functions, S3, and AWS Glue to operationalize AI workloads. The role also requires implementing RAG architectures using vector databases such as OpenSearch or FAISS to enhance retrieval accuracy in production AI systems.

A major responsibility is embedding AI governance and observability into every layer of the platform. This includes policy-as-code enforcement, audit-ready model lifecycle tracking, drift detection, and hallucination monitoring. You will also optimize system performance by managing token usage efficiency, compute cost control, and system latency improvements.

Additionally, you will collaborate with product, risk, and engineering stakeholders to translate business requirements into scalable AI solutions while ensuring compliance with financial industry standards.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a highly selective engineering leadership role requiring deep expertise in AI platform architecture. Candidates must demonstrate strong experience in scalable AI systems, cloud-native engineering, and regulated environments. Competition is intense due to the combination of fintech scale, AI specialization, and leadership expectations.

🚀 Career Impact

This role significantly accelerates career progression into AI leadership, platform architecture, and enterprise engineering strategy. It positions you for future executive-level engineering roles in fintech or large-scale AI infrastructure organizations.

📋 Key Responsibilities

You will be responsible for building and maintaining a scalable AI Ops platform that supports production AI workloads across merchant payments. Core duties include designing LLMOps pipelines, implementing secure CI/CD workflows for AI models, and ensuring seamless deployment of generative AI agents.

You will manage model lifecycle operations including evaluation, monitoring, drift detection, and rollback strategies. Additionally, you will enforce enterprise-grade security, governance, and compliance controls across all AI systems.

A critical part of the role involves optimizing infrastructure performance across AWS services, improving reliability through SRE principles, and reducing operational cost. You will also collaborate with cross-functional teams to translate business needs into scalable technical solutions while ensuring system resilience and auditability.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

This section is personalized by seniority.

How to use: Paste into ChatGPT, Claude, or Gemini

Writing here

…

Writing here

…

🧠 Fit & Positioning Analysis

Evaluate your match before applying.

📅 Application Signals

This role signals urgent demand for senior AI infrastructure talent in regulated financial environments. Competition is expected to be very high due to the combination of AI specialization, leadership expectations, and fintech scale. Candidates with proven enterprise AI deployment experience should prioritize early application to maximize visibility.

🔗 Apply for this Job

Apply on Company Site

✅ Job Source & Verification

This listing is sourced directly from a verified corporate careers page (Barclays Workday system), ensuring high authenticity and up-to-date hiring information. The role details reflect an official posting with structured responsibilities and leadership expectations. Last updated: May 2026, confirming current active recruitment status.