What you'll be doing:
Build and develop a full-stack automation platform (Python microservices backend, modern web frontend) used to generate, configure, and validate network topologies for AI/HPC data centers.
Implement scalable, reliable, and maintainable services and APIs that turn complex infrastructure requirements into validated, exportable network configurations.
Build and refine intuitive web interfaces that guide users through an interactive, step-by-step topology development workflow.
Collaborate closely with internal and external collaborators to understand requirements and deliver robust full-cycle solutions.
Improve stability and performance across the generation pipeline through architectural improvements and code optimizations.
Troubleshoot issues in distributed, containerized environments and contribute to system observability and reliability improvements.
Work cross-functionally with architects, DevOps engineers, product managers and collaborators to ensure high-quality releases.
Participate in code reviews, technical design discussions, and continuous improvement activities within the team.
What we need to see:
B.Sc. in Computer Science, Engineering, or a related field, or equivalent experience in practice.
5+ years of strong hands-on software development experience, primarily in Python.
Proven experience designing and building microservices and RESTful APIs (e.g., FastAPI, Flask, or Django).
Full-stack ability: practical experience with a modern frontend framework (Angular, React, or comparable) and TypeScript.
Solid experience on Linux-based platforms.
Experience with relational databases and data modeling (e.g., PostgreSQL/SQL).
Practical experience with containers and cloud-native technologies (Docker, Kubernetes/OpenShift).
Experience with version control systems (Git) and CI/CD pipelines.
Independent, fast learner with a strong sense of ownership, excellent debugging and problem-solving skills, and effective communication abilities.
Ways to stand out from the crowd:
Experience with agentic AI / LLM application development – orchestration frameworks (e.g., LangGraph), RAG, and vector databases (e.g., Qdrant).
Familiarity with large-scale network architectures, switches/routers, and common data center / AI cluster network topologies.
Hands-on experience with GitOps or equivalent experience and OpenShift/Kubernetes deployments.
Familiarity with DevOps methodologies and tools (e.g., Jenkins, Ansible).
