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Known brand, metro location, and mid-level requirement raise competition despite niche LLM skills.
Requires production ML/LLM engineering skills, limiting transferability outside AI-focused roles.
Mandates 4+ years plus production LLM/AI engineering and Python, making filters strict.
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Support customer engagements by executing configuration, integration, environment setup, and solution deployment tasks under guidance from senior engineers.
Own first-response incident management for assigned accounts including issue documentation, initial severity assessment, and escalation as needed.
Contribute to reusable configuration templates, technical documentation, and AI-enabled customer solution integrations including generative AI and ML workflows.
4+ years of professional experience in technical implementation or customer-facing roles.
Hands-on experience with LLM application development, prompt engineering, and function/tool calling.
Experience with AI agent orchestration frameworks like LangGraph or LangChain, and strong Python/software engineering skills for deploying and optimizing AI workloads.
Basic working knowledge of enterprise software platforms, APIs, integrations; capacity to work under structured guidance with clear communication.
Early-career technologist with proven ability to translate specified technical requirements into reliable delivered solutions in configuration and integration.
Experience with production AI engineering, especially around deploying, monitoring, and optimizing ML and LLM-based applications.
Comfortable working in structured, guided team environments with focus on quality, security, and performance, and contributing to reusable processes and documentation.