Lead AI Engineer (Agentic Systems)

About the role

Senior AI Engineer (Agentic Systems)  UK Based Role   At StarCompliance, 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 Lead 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.