How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior AI Engineer (Agentic Systems)
UK-Based
About the 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 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 (preferably Cursor) 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. In this culture, 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, rather than using 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
- Parallelization
- Apply AI across the lifecycle:
- Coding
- Testing
- Review
- Delivery
- Balance speed with control, operating safely within a regulated SaaS environment
- Deliver measurable improvements in through-put, quality, and developer experience
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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 (preferably Azure DevOps), 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
- Modern development practices
- Familiarity with CI/CD pipelines (preferably Azure DevOps)
AI & Agentic Engineering
- Hands-on experience using AI within real development workflows (unlike standalone tools)
- Deep familiarity with AI-native IDEs (preferably Cursor 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:
- 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
Get help with your application
Your very own career expert that helps elevate your application to the next level.
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 scaled those practices across teams.
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
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location