Darum lohnt es sich
Responsibilities Partner with enterprise customers to scope and implement AI Agent use cases across complex workflows Integrate IFS Loops platform with customer systems Tune agent behavior and logic to deliver measurable outcomes (e.g., lower costs, increase in efficiency, fewer errors) Troubleshoot deployments and iterate quickly to ensure performance, accuracy, and user adoption Collaborate closely with Product, Engineering, and Customer Success to feed customer insights into the roadmap Document technical decisions and hand off stable deployments to customer engineering or support teams Requirements 2–5 years of experience in a software engineering, solutions engineering, or ML deployment role Proficiency in Python and working knowledge of AI/ML frameworks (e.g.
OpenAI, Hugging Face, LangChain, Pinecone, Weaviate, etc.) Familiarity with building LLM applications, RAG systems, or conversational AI workflows Experience integrating with enterprise systems via APIs or middleware (e.g.
Salesforce, ServiceNow, SAP, Oracle) Ability to translate business problems into technical solutions—and deliver them fast Strong interpersonal skills; you’re just as comfortable on a whiteboard with a customer as you are in code Bias toward action, ownership, and continuous learning in dynamic environments
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