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AI agent security is the new AI security specialization for running autonomous LLM agents safely in production: runtime capability scoping, MCP tool-permission hardening, prompt-injection defense, and agent execution sandboxing.

The AI Evaluation Engineer proves with numbers whether LLM and agent systems actually work and whether they regressed. As benchmarks like SWE-bench Verified lost their signal to contamination, building trustworthy eval harnesses split off into its own role.

The On-Device ML Engineer runs models directly on phones, laptops, and edge hardware. As privacy rules, inference cost, and latency push inference off the server and onto the device, wiring up local inference with quantization, llama.cpp, and Core ML split off into its own role.

AI Workforce Transition Advisor: the consulting role that helps organizations manage the AI-driven reshaping of entry-level work through reskilling programs, role redesign, junior-talent pipelines, and change management. Grounded in a 35% drop in US entry-level postings and OpenAI's finding that 27% of EU jobs will reorganize.

As the EU Chat Control vote turns on-device content scanning into a regulatory mandate, demand surges for engineers who can scan while preserving privacy. Skills and career path explained.

A career guide to AI alignment research, where philosophy and ethics meet machine learning to keep frontier models pointed at what humans actually want.