Staff Backend Engineer

תל אביב
משרה קבועה
משרה מלאה

לפני 27 ימים

Loora AI is seeking a Staff Backend Engineer to drive the architecture and development of our AI-powered language learning platform. In this role, you will design and implement backend systems that directly impact millions of learners worldwide. You will architect scalable services that power real-time AI conversations, ensuring low-latency performance and reliability while building the foundation for our next generation of language learning features.Responsibilities:

Design, develop, and maintain high-performance backend services and APIs (REST and gRPC) that power AI-driven conversational experiences.
Build and optimize asynchronous Python applications capable of handling real-time audio/text processing at scale.
Ensure seamless, low-latency integration between mobile/web clients and our AI backend platform.
Drive technical decisions on system architecture, focusing on low latency and fault-tolerance.
Collaborate with AI/ML, mobile, DevOps, and product teams to deliver end-to-end solutions that delight our users.
Work within CI/CD workflows to ensure smooth deployments and maintain high code quality standards.
Establish engineering best practices and mentor team members to build a world-class engineering culture.
Optimize system performance and resource utilization while maintaining reliability SLAs for our growing user base.

Requirements:

Minimum of 6 years of diverse Python development experience
Deep expertise in Python concurrency and execution models (WSGI, ASGI, asyncio, multiprocessing, threading, GIL).
Proven track record building production-ready asynchronous Python applications serving high-volume traffic.
Strong experience with Pydantic and FastAPI in production environments.
Expertise in designing and implementing RESTful APIs and gRPC services with strong emphasis on versioning strategies and backward/forward compatibility.
Demonstrated ability to solve complex performance, scalability and workload distribution challenges.
Proficiency with relational and non-relational database solutions (PostgreSQL, Redis, DynamoDB, MongoDB) including query optimization and data modeling.
Experience with event-driven architectures and message queuing systems (Kafka, RabbitMQ, AWS SQS).
Hands-on experience with Docker, understanding of CI/CD pipelines and methodologies, and working in Kubernetes/AWS-based deployments.
Strong proficiency with AWS cloud services and cloud-native architectures.
Understanding of observability practices (distributed tracing, metrics, logging) and experience with monitoring tools.

Nice-to-Have:

Proficiency in additional backend programming languages (Go, Rust, Java, Scala, Kotlin).
Experience with audio/video streaming protocols and real-time communication systems.
Experience with dataframe libraries (Pandas, Polars, Daft) for data processing and analytics.
Familiarity with LLM integration libraries (LiteLLM, LangChain, Guidance, Instructor) and AI model serving frameworks.
Background in building data-driven applications, pipelines, or ETL processes using frameworks like Apache Spark / Flink and orchestration tools such as Airflow or Dagster.
Contributions to OSS projects on GitHub.

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