Key skills
CloudDockerJavaKafkaPythonScalaSparkSQLAIAgenticLangGraphSnowflakeDatabricksCI/CD
About this role
Role Overview
- architect context-rich AI solutions
- design, develop, and integrate intelligent systems focused on LLMs
- architect and optimize robust data pipelines
- integrate, fine-tune, and orchestrate LLMs within Python-based applications
- build and manage complex conversational and agent workflows using frameworks like LangGraph
- collaborate with product, data science, and engineering teams to define requirements and iterate on solutions
- implement testing, monitoring, and evaluation pipelines
Requirements
- expertise in full stack Python
- experience with a modern data and AI engineering technology stack (e.g., Spark, Kafka, Databricks, Snowflake, Java, Scala, SQL)
- demonstrated expertise in prompt engineering for LLMs
- strong understanding of context engineering
- hands-on experience integrating AI agents and LLMs into production systems
- proficiency with agentic/conversational flow frameworks such as LangGraph
- experience with cloud infrastructure, containerization (Docker), and CI/CD practices
- bachelor's level degree or equivalent in Computer Science, or related field of study
Tech Stack
- Cloud
- Docker
- Java
- Kafka
- Python
- Scala
- Spark
- SQL
Benefits
- competitive salary plus an annual company performance bonus
- wellness & leisure time contribution
- sickness compensation plan
- premium medical services
- family friendly benefits
- meal contribution
- extra days of vacation