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Mid-level, popular AI Engineer title and metro location increase competition despite niche LLM requirements.
Requires specialized ML systems and agentic LLM production experience, limiting cross-industry transferability.
Explicit years, mandatory ML systems and LLM skills, and cloud stack make filters strict.
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Develop and launch GenAI agentic solutions to reduce risk and cost in managing complex large-scale production environments.
Design and implement tool-calling agents and guardrails for safety, compliance, and secure action in production runtime.
Integrate AI agents with observability, incident management, and deployment systems to enable automated diagnostics and remediation with full traceability.
5+ years software development experience with Python, C/C++, Go, or Java.
3+ years experience designing, architecting, and launching production ML systems including model deployment and monitoring.
Practical experience integrating and applying Large Language Models (LLMs), including prompt engineering and tool-using agents.
Solid foundational knowledge of applied statistics, ML concepts, algorithms, and data structures.
Experienced in building scalable AI/ML solutions in large production environments, especially with LLM integration and agentic AI.
Demonstrates strong ownership and analytical problem-solving with ability to simplify complex ideas and deliver measurable business impact.
Familiarity with cloud infrastructure (preferably AWS) and modern deployment tools is a plus for success.