AI Engineer

4w1 month ago

SQLI

London, GB · Full-time · £70,000 – £95,000

About this role

SQLI is a European leader in digital transformation and customer experience, helping major international brands drive growth through technology. We design and deliver high-performance architectures and engaging digital experiences by combining advanced technologies, proven methodologies, and deep technical expertise.

The AI Engineer is the build engine of our AI practice, turning business requirements into working AI solutions using coding agents and frontier models. This is not a model-training role; you build agentic workflows and LLM-powered applications on top of frontier models, wire them into real enterprise systems, and make them safe to run.

You will work as part of the delivery team alongside consultants, business analysts, and architects. The consultant carries the client relationship and the architect owns the hard architectural calls, while you own the build and make real engineering decisions. You are proactive about spotting better ways to build and trusted to deliver without close supervision.

You will create reusable AI assets and accelerators for the practice, including skills, plugins, and MCP servers that make future engagements faster. You also support Data & AI teams with best practices around AI-assisted development, documentation, and automation, coaching less experienced colleagues on agentic build patterns and security standards.

Requirements

Proven experience with AI-assisted development — you have shipped something real with Claude or another agent platform, not just followed tutorials
Strong TypeScript and/or Python for agentic glue code, custom MCP work, and evaluation
Experience building RAG applications
Hands-on with creating and using agent plugins, skills, and MCP servers for repeatable agentic workflows
Skilled at engineering the prompts and context that let agents do work as autonomously as is safe and sensible
Solid grasp of security, access control, and data protection (including GDPR) when building systems that act against real client data with real permissions
Experience setting up CI/CD

Responsibilities

Use coding agents to prototype AI solutions quickly against real client requirements so the team can validate value before committing to a full build
Build, deploy, and maintain LLM-powered applications and agents that align with enterprise architecture principles with evaluation, monitoring, and token tracking in place from day one
Set up MCP connectors and permissions against client systems, taking real care over data handling, access control, and what an agent is allowed to do
Build production solutions that meet client security requirements and European data protection obligations, including GDPR
Collaborate with consultants, business analysts, and architects to break business requirements into solutions that are feasible, maintainable, and safe
Create reusable AI assets and accelerators for the practice, including skills, plugins, and MCP servers that make future engagements faster
Support Data & AI teams with best practices around AI-assisted development, documentation, and automation, and coach less experienced colleagues on agentic build patterns and security standards
Document deployment, upgrade paths, and maintenance so SQLI and clients can own what you build after handover

Benefits

Work as part of a delivery team alongside consultants, business analysts, and architects
Own the build and make real engineering decisions, not just execute someone else's spec
Create reusable AI assets and accelerators that make future engagements faster
Support and coach less experienced colleagues on agentic build patterns and security standards