Lead AI Engineer (Agentic Systems)

StarCompliance; United Kingdom; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading compliance solutions provider in the UK is seeking a Senior AI Engineer to enhance their software development lifecycle through the practical application of AI. Responsibilities include designing AI-assisted workflows, integrating AI into CI/CD pipelines, and driving the adoption of AI practices across engineering teams. Ideal candidates will possess a strong software engineering background, significant experience with AI in development workflows, and expertise in cloud-based SaaS environments.

Qualifications

• Experience designing and evolving enterprise-scale distributed systems.
• Practical experience applying AI within professional engineering workflows.
• Demonstrated impact in improving engineering delivery or developer productivity.

Responsibilities

• Design and implement scalable AI-assisted engineering workflows across teams.
• Integrate AI into CI/CD pipelines including autonomous code review.
• Work directly within codebases to accelerate delivery and improve quality.

Skills

Strong software engineering background (C# / .NET)

Experience building and operating distributed systems

Hands-on experience using AI in development workflows

Experience with CI/CD pipelines (Azure DevOps)

Problem-solving skills in complex environments

Education

Software engineering experience in cloud-based SaaS

Experience in enterprise-scale distributed systems

Tools

Cursor IDE

Azure DevOps

Job description

Overview

UK Based Role. At StarCompliance, we build software that supports critical compliance needs for global clients. We are 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 StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.