Senior AI Engineer (Agentic Systems)

Overview

Senior AI Engineer (Agentic Systems)

UK Based

Role

At [Employer hidden], we build software that supports critical compliance needs for global clients. We are now embedding AI as a core capability across the entire software development lifecycle.

We are seeking a Senior AI Engineer to lead the practical adoption and scaling of AI-assisted and agentic engineering across our teams.

This is not a research or experimentation role. You will work hands-on within real codebases, using modern AI-native development environments (Cursor preferred) to fundamentally change how software is built, tested, and delivered. Your focus is to turn AI from a tool into a system. Repeatable, scalable, and embedded.

You will define and implement playbooks, patterns, and workflows that enable teams to operate with parallel AI agents, autonomous code review, and AI-driven delivery pipelines. You will also help bootstrap new initiatives, ensuring they start with the right architecture, tooling, and AI-enabled engineering practices from day one.

This role sits within R&D Engineering and partners closely with Platform, QA, and Product Engineering. Influence is earned through delivery, not hierarchy.

How We Think About AI

AI is not an assistant. It is part of the engineering system. We expect engineers in this role to:

• Embed AI directly into development workflows, not use it as a separate tool
• Design repeatable, production-grade AI workflows, not one-off prompts
• Leverage agentic patterns such as multi-step execution, tool chaining, and parallelization
• Apply AI across the lifecycle: coding, testing, review, and delivery
• Balance speed with control, operating safely within a regulated SaaS environment
• Deliver measurable improvements in throughput, quality, and developer experience

Responsibilities

Design and implement scalable AI-assisted engineering workflows across teams

Establish playbooks, standards, and best practices for agentic development

Build and operationalize:

• Task-specific agents (e.g. test generation, refactoring, code analysis)
• Reusable skills, templates, and workflows
• Multi-agent and parallel execution patterns

Integrate AI into CI/CD pipelines (Azure DevOps preferred), including:

• Autonomous or assisted code review
• AI-driven test generation and maintenance
• Code quality and compliance checks

Implement automation triggers and hooks to embed AI into the delivery lifecycle

Work directly within codebases to accelerate delivery and improve quality

Enable and upskill engineering teams through practical guidance, examples, and training

Bootstrap new projects with AI-first engineering practices and tooling

Rapidly prototype and validate new approaches, focusing on real delivery impact

Ensure all AI-enabled workflows are robust, observable, and production-safe

Skills and Experience

Core Engineering

• Strong software engineering background (ideally C# / .NET) in cloud-based SaaS environments
• Experience building and operating distributed systems
• Strong understanding of APIs, system design, and modern development practices
• Experience with CI/CD pipelines (Azure DevOps preferred)

AI & Agentic Engineering

• Hands-on experience using AI within real development workflows (not standalone tools)
• Deep familiarity with AI-native IDEs (Cursor preferred, or similar)
• Proven experience designing structured AI workflows, including:
• Reusable prompts, skills, or templates
• Multi-step or agent-based execution patterns
• Tool integration and workflow orchestration
• Experience integrating AI into engineering systems, such as:
• CI/CD pipelines
• PR validation and automation
• Developer tooling
• Practical application of AI to:
• Test generation and maintenance
• Code analysis, refactoring, and quality improvement
• Developer productivity at scale

Delivery & Problem Solving

• Track record of delivering production-grade solutions, not just prototypes
• Experience enabling other engineers or teams to adopt new technologies at scale
• Strong problem-solving skills in complex, evolving environments
• Ability to define patterns where none exist and make them usable by others

Important Clarification

Experience limited to prompt-based tools used in isolation is not sufficient.

We are looking for engineers who have embedded AI into real engineering systems and workflows and have scaled those practices across team

Minimum Qualifications

Software engineering experience in cloud-based SaaS environments

Experience designing and evolving enterprise-scale distributed systems

Demonstrated impact in improving engineering delivery or developer productivity

Practical experience applying AI within professional engineering workflows

Experience working within enterprise SaaS platforms

Right to work in the country of employment

Integrity and Ethics

All [Employer hidden] employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.