Backend Engineer
AppsflyerHerzliyaот 3 лет
PythonSQLAIPostgreSQLKubernetesCI/CDDockerLLMBackendAPIAWSGoMicroservicesNode.jsAirflowGCPSparkNoSQLS3SnowflakeScalaBigQuery
Описание
AppsFlyer's Data Services group is looking for a talented Backend Developer to help shape their next-generation data export solutions. The team's mission is to give customers and partners a secure, reliable, and flexible way to get their data. The core product, DataLocker, delivers data reports on flexible schedules to stores like S3, BigQuery, and Snowflake. The team also owns the AI Assistant, a conversational assistant built into the AppsFlyer platform, powered by LLMs, multi-agent orchestration, and MCP. The stack includes Scala, Python, PostgreSQL, Spark, Airflow, LLMs, MCP and more.
Responsibilities
- Build and scale backend data export services and pipelines, integrating with various 3rd party vendors and data stores
- Build and evolve the AI Assistant backend: agent orchestration, tool integrations over MCP, and secure human-in-the-loop actions on customer data
- Own and develop products and features end-to-end, from design to production
- Process and deliver massive data volumes reliably, efficiently, and securely
- Collaborate with Product Managers and Software Engineers to deliver value to customers
- Continuously learn and evaluate new technologies to adapt to ever-growing scale
Requirements
- 3+ years of backend development experience
- Strong experience in Scala, Java, Python, or a similar language
- Experience with cloud platforms (AWS, GCP), data stores and warehouses (such as S3, BigQuery, Snowflake), and access permissions
- Hands-on experience with Spark and Airflow, or similar big data and orchestration tools
- Experience building and optimizing APIs and data-intensive services on large-scale databases (PostgreSQL preferred)
- Hands-on exposure to LLMs (prompting, tool calling) and interest in building AI-powered features
- B.Sc. in Computer Science or equivalent
Nice to have
- Experience with large-scale data pipelines and streaming
- Experience building LLM-based applications or agents (RAG, agent frameworks, MCP)
- Experience with data lake formats (such as Parquet, Delta, Iceberg)