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Mid-level experience, metro location, and recognizable analytics brand create moderate applicant competition.
Requires specialized LLM and production AI engineering skills, making cross-industry fit highly domain-sensitive.
Explicit 4+ years plus mandatory LLM, agent frameworks, production AI engineering, and Python tightens shortlisting.
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Analyze and resolve complex customer engineering issues by building AI-driven automation tools and workflows.
Develop, test, and optimize LLM-based solutions for troubleshooting and preventing customer problems, enhancing reliability and efficiency.
Collaborate with internal teams to integrate AI capabilities into existing tools, measure performance using engineering metrics, and establish scalable AI application patterns.
4+ years of experience in technical implementation or customer-facing technical roles.
Hands-on experience with LLM application development including prompt engineering and function/tool calling.
Proficiency in Python and production AI engineering: deployment, monitoring, evaluation, and optimization of AI workloads.
Basic knowledge of enterprise software platforms, APIs, integrations; ability to document and maintain technical solutions.
Experienced in building agentic AI workflows using frameworks like LangGraph or LangChain with multi-component tool integrations.
Comfortable operating in structured team environments with clear guidance and communicating technical progress to diverse stakeholders.
Strategic in improving AI solutions via iterative testing and validation focused on measurable engineering outcomes like accuracy and latency.