AI Implementation Engineer

Design, test, and implement solutions using available technologies and tools in the fields of AI, low-code, etc., to optimize business processes.
Participate in identifying and developing solutions, as well as gathering requirements for implementing AI in business processes.
Propose relevant solutions and keep up with industry trends.
Analyze the effectiveness of implemented automations and identify opportunities for improvement.
Conduct internal training sessions on tools and approaches in the field of AI.

1–2 years of experience implementing AI automations in roles related to AI adoption.
Proven use cases involving large language models, knowledge base search, or classification tasks.
Proficiency with the tech stack: OpenAI / Anthropic APIs, Python, databases, and orchestration tools for building multi-step AI pipelines.
Experience with no-code / low-code automation platforms (Make, n8n, Zapier) for rapid automation setup.
Strong prompt engineering skills for production-scale use (output format control, exception handling, result validation, and reduction of model errors and hallucinations).
Experience in requirements elicitation, strong communication skills, and a proactive mindset.

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