AI Deployment Engineer

• We will rely on you to own the data infrastructure underpinning our AI deployments, including pipelines, storage, and data serving.
• You will integrate AI solutions into our business ecosystem, including CRMs, ERPs, SaaS tools, and internal systems.
• You will build and maintain APIs, webhooks, and middleware that allow AI agents to interact with business systems.
• You will take strategist-built prototypes to production-grade solutions by hardening, scaling, and ensuring reliability.
• You will set up monitoring, logging, and alerting across deployed pipelines and agent infrastructure.
• You will manage data models, schemas, and storage to support current and future AI deployments.
• You will troubleshoot integration failures, data inconsistencies, and production issues.
• You will serve as the deep technical engine behind our internal AI deployment team, ensuring our AI tooling works reliably at scale.

Technologies:

• AI
• Airflow
• AWS
• Azure
• Backbone
• Claude Code
• Cloud
• Copilot
• Docker
• Flink
• GCP
• Support
• Kafka
• Kubernetes
• Microsoft 365
• OAuth
• Python
• REST
• RPA
• SQL
• UiPath
• dbt
• Office 365
• DevOps, We are a global FinTech with offices around the world, including Bristol and London. This AI Deployment Engineer role can be based in either our Bristol or London office, with a hybrid working model of around three days per week in the office and some flexibility for the right candidate. We offer a salary of £80,000 to £130,000 per annum depending on experience, plus excellent benefits. In this role, you will work closely with our internal AI deployment team to build the technical backbone that supports reliable, production-scale AI solutions.

• We are looking for 3-5 years of experience in software engineering or data engineering, with strong exposure to system integrations, data pipelines, and production infrastructure.
• We need strong Python and SQL skills, with experience building robust, production-grade data pipelines from scratch.
• We require deep familiarity with integration patterns, including REST APIs, webhooks, OAuth, and event-driven architectures.
• We need experience with orchestration tools such as Airflow, Prefect, or Dagster, and transformation frameworks such as dbt or similar.
• We require comfort working across cloud platforms such as AWS, GCP, or Azure, and with containerisation technologies such as Docker and Kubernetes.
• We need experience connecting disparate business systems, including SaaS platforms, internal databases, and third-party APIs, and making them work reliably.
• We value strong debugging instincts and a high bar for reliability and data integrity.
• We need comfort with Microsoft 365 and Microsoft Copilot; familiarity with AI productivity tools such as Claude Code, Claude Cowork, and Claude Skills is a plus.
• We require a bachelors degree in Computer Science, Engineering, or equivalent practical experience.
• Desirable experience includes vector databases and embedding pipelines, real-time streaming technologies such as Kafka or Flink, and RPA tooling such as UiPath or Power Automate.