At a Glance
- Tasks: Lead the integration of AI into software development, enhancing workflows and delivery.
- Company: Join StarCompliance, a leader in compliance software with a focus on innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on ethical practices and integrity.
- Why this job: Transform how software is built using cutting-edge AI technology and make a real impact.
- Qualifications: Strong software engineering background and hands-on AI experience in development workflows.
The predicted salary is between 70000 - 90000 € per year.
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 (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
- 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:
- PR validation and automation
- 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 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
All StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner.
Agentic AI Engineer employer: StarCompliance
At StarCompliance, we pride ourselves on fostering a dynamic work culture that champions innovation and collaboration. As an employer, we offer our employees the opportunity to work at the forefront of AI technology within a supportive environment that encourages professional growth and development. Our commitment to integrity and ethical practices ensures that every team member can contribute meaningfully to impactful projects while enjoying a balanced work-life experience.
StudySmarter Expert Advice🤫
We think this is how you could land Agentic AI Engineer
✨Tip Number 1
Get your hands dirty! Dive into coding challenges or projects that showcase your AI skills. This is your chance to demonstrate how you can embed AI into real workflows, just like the role at StarCompliance requires.
✨Tip Number 2
Network like a pro! Connect with current employees at StarCompliance on LinkedIn or attend industry meetups. Building relationships can give us insights into the company culture and what they really value in candidates.
✨Tip Number 3
Prepare for hands-on interviews! Expect to solve real problems using AI in coding tasks. Brush up on your C# and .NET skills, and be ready to discuss how you've integrated AI into your past projects.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team at StarCompliance.
We think you need these skills to ace Agentic AI Engineer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Agentic AI Engineer role. Highlight your experience with AI in real development workflows and how you've embedded it into engineering systems. We want to see how you can bring your unique skills to our team!
Showcase Your Projects:Include specific examples of projects where you've implemented AI-assisted engineering workflows. We love seeing tangible results, so mention any measurable improvements in throughput or quality that came from your work. This helps us understand your impact!
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to describe your skills and experiences. We appreciate a well-structured application that makes it easy for us to see why you're a great fit for the role.
Apply Through Our Website:Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StarCompliance!
How to prepare for a job interview at StarCompliance
✨Know Your AI Inside Out
Make sure you’re well-versed in how AI integrates into engineering workflows. Be ready to discuss specific examples of how you've embedded AI into real codebases, not just theoretical knowledge. This will show your hands-on experience and understanding of the role.
✨Demonstrate Your Engineering Skills
Brush up on your software engineering fundamentals, especially in C# and cloud-based SaaS environments. Be prepared to talk about your experience with distributed systems and CI/CD pipelines, as these are crucial for the role.
✨Prepare for Problem-Solving Scenarios
Expect to face complex problem-solving questions during the interview. Think of scenarios where you’ve had to define patterns or improve delivery processes. Show how you can balance speed with control while working within a regulated environment.
✨Showcase Your Collaborative Spirit
Since this role involves partnering closely with various teams, be ready to discuss how you’ve enabled others to adopt new technologies. Highlight any experiences where you’ve provided practical guidance or training to help teams scale their AI practices.
