Client-Facing AI Deployment Engineer

CloudFactory; Reading; On-site; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Relocation assistance

Frequent travel to client sites

Job summary

CloudFactory is seeking an engineering professional to join our AI enablement platform and work directly with strategic clients to design and implement scalable integrations, define production-ready workflows, and ensure AI systems move from experimentation to reliable deployment. This hands-on role blends engineering depth with customer-facing responsibilities.

You will build APIs, data pipelines, and automation that power AI at scale while partnering with Delivery teams to reduce risk, improve

Qualifications

• 2+ years software engineering experience.
• Strong proficiency in Python, Go.
• Proficiency with Claude and all relevant AI tools.
• Experience with cloud infrastructure (AWS/GCP/Azure).
• Experience building APIs and working with distributed systems.
• Experience designing data pipelines or ML infrastructure.
• Strong prioritization and product judgment.

Responsibilities

• AI Deployment Architecture: design and implement integrations between client systems and CloudFactory’s platform.
• Product Readiness & Scale: translate proof-of-concept AI systems into scalable production workflows and identify risks.
• Hands-on Engineering: build APIs, connectors, automation scripts, and data pipelines; debug issues.
• Field Product Intelligence: surface recurring patterns from client deployments and influence roadmap priorities.
• Technical Leadership: lead technical discovery sessions and support pre-sales validation.
• Engineering depth: contribute to platform improvements and understand end-to-end AI lifecycle.

Skills

Python

Go

Claude

AI Tools

APIs

Distributed Systems

Data Pipelines

Cloud Platforms

Technical Leadership

Tools

AWS

GCP

Azure

Job description

CloudFactory is seeking an engineering professional to join our AI enablement platform and work directly with strategic clients to design and implement scalable integrations, define production-ready workflows, and ensure AI systems move from experimentation to reliable deployment. This hands-on role blends engineering depth with customer-facing responsibilities.

You will build APIs, data pipelines, and automation that power AI at scale while partnering with Delivery teams to reduce risk, improve