StarCompliance - Senior AI Engineer (Agentic Systems)
Requirements
• 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: • 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 • Practical application of AI to: • Test generation and maintenance • Code analysis, refactoring, and quality improvement • 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 • 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
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 • 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.
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