Back
Mid-level generalist backend role with broad platform requirements increases competition.
Backend and platform skills transfer across industries, though AI integration raises domain specificity.
Explicit 5–7 years requirement and mandatory Python/backend stack enforce strict screening.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and maintain backend APIs and long-running workflow execution systems for engineering automation.
Develop reliable data handling, artifact versioning, and platform reliability including deployment and monitoring in Linux/Docker environments.
Integrate backend services with AI/ML platforms and collaborate closely with algorithm and domain engineers to transform workflows into maintainable software.
5-7 years of professional software engineering experience.
Strong Python backend development skills with experience in FastAPI, Flask, Django, or similar frameworks.
Experience with background job processing, queues (Celery, Redis, or equivalents), async processing, and workflow orchestration.
Docker and Linux deployment experience; strong debugging, testing, and data modeling skills.
Engineer experienced in building scalable backend platforms with workflow automation and data/artifact management.
Comfortable with integrating AI/ML services and working in complex, ambiguous platform environments requiring end-to-end ownership.
Background or interest in AI infrastructure, large language model integration, and engineering automation workflows.