Position Overview:
We’re looking for a Backend Developer (Python-focused) to join our Engineering team at Aldataset and help us build a robust, scalable, and secure backend that powers our AI data platform and marketplace. You’ll design and implement services that handle massive datasets, real-time processing pipelines, authentication, billing, and integrations with AI/ML workflows.
This role is perfect for a backend engineer who loves writing clean Python code, cares deeply about performance and reliability, and wants to work at the intersection of data, AI, and scalable systems.
Key Responsibilities:
- Design, develop, and maintain high-performance backend services and APIs using Python (FastAPI / Django / Flask).
- Build and optimize data processing pipelines (ETL/ELT) for large-scale structured and unstructured datasets.
- Implement secure authentication/authorization systems (OAuth2, JWT, OpenID Connect) and role-based access control.
- Integrate with cloud services (Azure, AWS, GCP), object storage (S3, Azure Blob), queues (Celery, RabbitMQ, Redis), and databases (PostgreSQL, MongoDB, Elasticsearch).
- Develop and expose clean, well-documented REST and GraphQL APIs consumed by web and mobile clients.
- Write unit/integration tests, set up CI/CD pipelines, and ensure observability (logging, tracing, metrics).
- Collaborate closely with Data Engineers, ML Engineers, Frontend, and DevOps teams.
- Participate in architecture discussions and tech debt refactoring.
- Monitor production systems and respond to incidents (we have on-call rotation with fair compensation).
- Continuously improve code quality, security, and performance.
Requirements:
- 3+ years of professional backend development experience with strong Python skills.
- Deep experience with at least one modern Python web framework (FastAPI strongly preferred; Django/Flask also welcome).
- Solid understanding of relational databases (PostgreSQL) and NoSQL solutions.
- Experience with async programming (asyncio, FastAPI, Starlette) and working with large datasets.
- Proficiency with Git, Docker, CI/CD (GitHub Actions, GitLab CI, Azure DevOps), and Linux environments.
- Familiarity with cloud platforms (Azure is a big plus) and Infrastructure-as-Code basics.
- Strong grasp of API design principles, OpenAPI/Swagger, testing (pytest), and code quality tools.
- Good command of English (reading/writing technical docs); Persian is helpful for team syncs.
- Genuine excitement about building the backbone of an AI data platform.
Bonus Points:
- Experience with data pipeline tools (Airflow, Prefect, Dagster)
- Knowledge of ML model serving (FastAPI + ONNX/TensorFlow/PyTorch)
- Background in search engines (Elasticsearch, OpenSearch) or vector databases (Pinecone, Weaviate, Qdrant)
- Contributions to open-source Python projects or visible GitHub profile
- Previous work in data marketplaces, labeling platforms, or AI companies