Python Engineer

Speaking Tutor is an AI-powered English learning application for students and teachers. The platform enables learners to have conversations with a virtual teacher, receive pronunciation assessment, and get detailed feedback after each conversation. The product combines language learning, speech evaluation, AI-driven interaction, and teacher-facing learning insights.

• 3–5+ years of professional experience in Python backend development.
• Solid understanding of REST API design and OpenAPI standards.
• Experience with asynchronous processing and queue-based architectures, e.g. Celery, SQS.
• Experience with libraries and frameworks such as FastAPI, Pydantic, SQLAlchemy, boto3.
• Hands-on experience with core AWS services such as Lambda, API Gateway, S3, CloudFront, Secrets Manager, IAM, ECS/EKS, CloudWatch.
• Good knowledge of DynamoDB and NoSQL data modelling.
• Good knowledge of PostgreSQL, SQL, and relational data modelling.
• Experience with both serverless (Lambda) and containerized (ECS/EKS) deployment models.
• Experience integrating with external APIs and third-party services.
• Experience with pytest and automated testing practices.
• Familiarity with CI/CD tools such as GitHub Actions and/or Jenkins.
• Experience with observability tools such as New Relic and CloudWatch.
• Understanding of distributed systems, scalability, reliability, and fault tolerance.
• Ability to apply SOLID principles, clean code practices, and common design patterns.
• Practical understanding of LLM-based applications or AI agentic frameworks.
• Ability to use AI development tools such as Cursor, Claude Code, or GitHub Copilot.
• Experience working in agile software development teams.
• Fluent English, both written and spoken.

• Design, build, and maintain backend services using Python in an AWS-based environment.
• Develop and maintain REST APIs together with clear OpenAPI documentation.
• Implement asynchronous processing and queue-based communication between services.
• Design data access patterns for application features using NoSQL and SQL storage.
• Integrate backend services with internal systems, external APIs, and AI/LLM-based components.
• Implement reliable communication patterns, including retries, timeouts, and circuit breakers.
• Build and maintain operational CLI tooling for day-to-day platform tasks (e.g. content ingestion).
• Contribute to architectural decisions across software and infrastructure as the stack evolves.
• Create observability for distributed systems, including logging, metrics, tracing, and alerting.
• Write automated tests and support high code quality across the backend codebase.
• Contribute to CI/CD processes and deployment automation.
• Collaborate with product, frontend, QA, DevOps, AI/ML teams, and content creators.
• Review code, share knowledge, and raise the bar for engineering practice across the team.

We reserve the right to contact the selected candidates.