Lead AI Engineer (Agentic Systems)

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.