AI Deployment Engineer

A leading technology-focused organisation is seeking an experienced AI Deployment Engineer to join its growing AI and data function. This is a highly technical, hands-on role forming the backbone of the company’s AI deployment capability, responsible for taking AI-driven solutions from prototype through to fully scalable, production-grade systems. Working closely with AI Strategists and product stakeholders, the AI Deployment Engineer will own the underlying infrastructure that enables AI systems to operate reliably across the business. The role is predominantly remote, with occasional on-site collaboration days in London.

Key Responsibilities:

• Own and develop the data and integration infrastructure supporting AI deployments, including pipelines, storage and data delivery layers.
• Design and implement robust integrations between AI solutions and core business systems (CRM, ERP, SaaS platforms and internal tools).
• Build and maintain APIs, webhooks and middleware to enable seamless system-to-system communication.
• Take AI prototypes into production by hardening, scaling and optimising for reliability and performance.
• Implement monitoring, logging and alerting across all deployed pipelines and AI services.
• Manage data structures, schemas and transformation logic supporting ongoing and future AI initiatives.
• Troubleshoot and resolve production issues, including integration failures and data inconsistencies.

Required Skills & Experience:

• 3–5+ years’ experience in software engineering, data engineering, or similar infrastructure-focused roles.
• Strong programming ability in Python and SQL, with experience building production-grade data pipelines.
• Solid understanding of integration patterns including REST APIs, webhooks, OAuth and event-driven architectures.
• Experience with orchestration tools such as Airflow, Prefect or Dagster.
• Familiarity with cloud environments (AWS, GCP or Azure).
• Experience with containerisation tools such as Docker and Kubernetes.
• Proven experience integrating multiple business systems and ensuring reliable data flow between platforms.
• Strong troubleshooting skills with a focus on system reliability and data integrity.
• Experience working with Microsoft 365 and exposure to AI productivity tooling is advantageous.
• Vector databases and embedding-based pipelines.
• Real-time data streaming technologies (e.g. Kafka, Flink).
• RPA tools such as UiPath or Power Automate.
• Data transformation tools such as dbt.
• Exposure to modern AI tooling and frameworks (e.g. Claude-based developer tools).

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Additional Information:

• This is a senior technical role within a forward-thinking AI team, offering the opportunity to shape and scale production AI systems within a complex enterprise environment.
• The position is fully remote with occasional travel to London for collaboration sessions.
• The organisation encourages innovation, ownership, and technical excellence, making it ideal for an engineer who enjoys solving complex infrastructure and integration challenges at scale.