Darum lohnt es sich
Lead the engineering and operational excellence behind our data collaboration ecosystem Design and implement scalable data architectures and drive automation through AI agents and self‑service tooling Build production‑grade software, reusable Python libraries, and AI‑enabled automation systems Mentor engineers through code reviews, technical design discussions, and operational best practices Collaborate with product, engineering, operations, and data platform teams to translate repeatable business needs into scalable technical solutions Requirements Bachelor’s degree or equivalent practical experience in Computer Science, Information Systems, Software Engineering, Electrical Engineering, Electronics Engineering, or a related technical field 5+ years of experience building production‑grade software using Python, including libraries, services, testing, CI/CD, and code reviews Hands‑on experience building applications using LLMs, RAG, vector databases, prompt engineering, or frameworks such as LangChain, LangGraph, LlamaIndex, or similar tools Experience designing AI‑enabled workflows, reasoning agents, tool‑using agents, or complex automation systems 3+ years of hands‑on experience with cloud data platforms such as Snowflake, Databricks, or similar technologies Strong understanding of production system design, including observability, reliability, scalability, performance tuning, and operational support Core Competencies Demonstrates expertise in building production‑grade software with Python, designing scalable data architectures, and implementing AI‑enabled automation systems. xayajpt Proven ability to mentor engineers and collaborate across teams to deliver effective technical solutions.
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