AI Deployment Engineer

Our client is a Global FinTech with offices around the world inc Bristol and London in the UK .<br />This AI Deployment Engineer role can be based out of Bristol or London offices.<br />Ideally 3 days per week in the office but could be a little bit more flexible for the ideal candidate.

• AI Deployment Engineer
• Location: Bristol or London - Hybrid, 3 days in the office
• Salary: £80,000 - £130,000 p/a dependent on experience + excellent benefits<br />You will be the deep technical engine behind their internal AI deployment team. Where the AI Deployment Strategist scopes and builds agents, you own the infrastructure underneath — data pipelines, system integrations, and everything that ensures deployed AI solutions work reliably at scale.<br />You will take prototypes to production, ensure all business systems communicate correctly, and build the technical backbone that our AI tooling depends on.<br />Job Responsibilities<br />• Own the data infrastructure underpinning AI deployments — pipelines, storage, and data serving<br />• Integrate AI solutions into the existing business ecosystem: CRMs, ERPs, SaaS tools, and internal systems<br />• Build and maintain APIs, webhooks, and middleware that allow AI agents to interact with business systems<br />• Take Strategist-built prototypes to production-grade — hardening, scaling, and ensuring reliability<br />• Set up monitoring, logging, and alerting across deployed pipelines and agent infrastructure<br />• Manage data models, schemas, and storage supporting current and future AI deployments<br />• Troubleshoot integration failures, data inconsistencies, and production issues<br />Key Skills<br />• Python &amp; SQL (production-grade pipeline development)<br />• REST APIs, webhooks, OAuth, event-driven architecture<br />• Orchestration tools: Airflow, Prefect, or Dagster<br />• Cloud platforms: AWS, GCP, or Azure<br />• Docker &amp; Kubernetes Microsoft 365 &amp; Microsoft Copilot<br />Desirable Skills<br />• Vector databases and embedding pipelines<br />• Real-time streaming (Kafka, Flink)<br />• RPA tooling (UiPath, Power Automate) dbt for data transformation<br />• Claude Code, Claude Cowork, or Claude Skills<br />• Experience with vector databases, real-time streaming (Kafka, Flink), or RPA tooling (UiPath, Power Automate).<br />Experience<br />• 3–5 years in software or data engineering with strong exposure to system integrations, data pipelines, and production infrastructure.<br />• Strong Python and SQL skills; experienced building robust, production-grade data pipelines from scratch.<br />• Deep familiarity with integration patterns: REST APIs, webhooks, OAuth, and event-driven architectures.<br />• Experience with orchestration tools (Airflow, Prefect, or Dagster) and transformation frameworks (dbt or similar).<br />• Comfortable across cloud platforms (AWS, GCP, or Azure) and with containerisation (Docker, Kubernetes).<br />• Experience connecting disparate business systems — SaaS platforms, internal databases, and third-party APIs — and making them work reliably.<br />• Strong debugging instincts and a high bar for reliability and data integrity.<br />• Comfortable with Microsoft 365 and Microsoft Copilot. Familiarity with AI productivity tools including Claude Code, Claude Cowork, and Claude Skills is a plus.<br />Qualifications<br />• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience<br />Python &amp; SQL (production-grade pipeline development)<br />• REST APIs, webhooks, OAuth, event-driven architecture<br />• Orchestration tools: Airflow, Prefect, or Dagster<br />• Cloud platforms: AWS, GCP, or Azure<br />• Docker &amp; Kubernetes Microsoft 365 &amp; Microsoft Copilot<br />• Vector databases and embedding pipelines<br />• Real-time streaming (Kafka, Flink)<br />• RPA tooling (UiPath, Power Automate) dbt for data transformation<br />• Claude Code, Claude Cowork, or Claude Skills<br />• Experience with vector databases, real-time streaming (Kafka, Flink), or RPA tooling (UiPath, Power Automate).<br />Python &amp; SQL (production-grade pipeline development)<br />• REST APIs, webhooks, OAuth, event-driven architecture<br />• Orchestration tools: Airflow, Prefect, or Dagster<br />• Cloud platforms: AWS, GCP, or Azure<br />• Docker &amp; Kubernetes Microsoft 365 &amp; Microsoft Copilot<br />• Vector databases and embedding pipelines<br />• Real-time streaming (Kafka, Flink)<br />• RPA tooling (UiPath, Power Automate) dbt for data transformation<br />• Claude Code, Claude Cowork, or Claude Skills<br />• Experience with vector databases, real-time streaming (Kafka, Flink), or RPA tooling (UiPath, Power Automate). London bristol bristol london fintech finance bank artificial intelligence artificial intelligence