The Project: Internal Support Tools Evolution
You are joining an initiative focused on the evolution, modernization of the Internal Application Landscape. This project involves the strategic transition of well-known cloud services and legacy .NET architectures into a next-generation, AI-augmented, and cloud-native software landscape.
Our goal is not simply to «maintain» the existing system, but to proactively transform it—ensuring sovereignty, high-performance scalability, and seamless handover readiness through disciplined engineering.
Our Engineering Philosophy
We operate at the intersection of Legacy Stability and Modern Innovation. Our approach is defined by:
AI-Augmented Engineering: We utilize advanced AI development environments (such as Cursor, Windsurf, and Claude Code) and cutting-edge model families to accelerate code comprehension, refactoring, and documentation.Disciplined SDLC Patterns: We move beyond traditional development by implementing repeatable, evidence-based SDLC patterns. Every change is backed by structured engineering evidence and rigorous automated testing.The "Strangler Fig" Modernization: We prioritize risk-mitigated evolution, using sophisticated patterns to wrap, refactor, and eventually replace legacy components.High-Seniority Autonomy: We operate as a lean, highly autonomous unit. We value "technical detectives" who can navigate ambiguity and perform deep reverse engineering.Mission
To build the automated safety net that makes our modernization efforts possible. You will ensure that as we evolve the Internal Application Landscape, we maintain absolute functional parity and prevent any regressions in our mission-critical business logic.
Role Focus
This role focuses on building scalable automation frameworks and implementing AI-driven testing strategies. You will verify that modernized components produce identical business outcomes to the legacy systems they replace, using both traditional and AI-augmented testing techniques.
Automated Regression & Parity Testing: Design and maintain comprehensive automated regression suites to protect legacy functionality and verify functional parity during migration.AI-Augmented Testing: Leverage AI-powered tools for automated test generation, self-healing test scripts, and intelligent visual regression testing.Framework Development: Build and optimize scalable automation frameworks (UI, API, and Integration levels) specifically tailored for .NET and modern cloud-native environments.Continuous Testing (CI/CD): Integrate automated test suites into DevOps pipelines (GitLab/GitHub/Jenkins) to provide immediate, high-confidence feedback.API & Integration Testing: Validate complex data flows and integrations between legacy monoliths and new, modern services.Collaboration: Work side-by-side with Developers and Architects to identify "testable" areas in legacy code and advocate for improved testability.
