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Niche production-AI requirements reduce applicants, but popular AI Engineer title keeps competition moderate.
Role requires specialized production AI and infrastructure experience, limiting cross-industry transferability.
No explicit years but strong production-AI and systems requirements necessitate technical filters.
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Own development and automation of engineering workflows using AI coding agents and MCP-connected tools as primary building methods.
Build and ship production code for live products including XgenPlus, ZenithAI, RajMail, TeamPortal, and new AI-native tooling under the FORGE methodology.
Manage systems with real operational stakes: mail platform securing 50M+ mailboxes at 99.9% uptime, on-premises AI platform for data sovereignty, and government infrastructure with high reliability requirements.
No strict degree or years of experience requirements; capability and curiosity prioritized over resume.
Work Experience Required: Not explicitly mentioned in the JD.
Technical skill in AI-driven software engineering, automation, and production system development implied but not explicitly quantified.
Location or onsite requirements: Not explicitly mentioned in the JD.
Experienced in end-to-end engineering of high-stakes, high-availability infrastructure or AI-native tools.
Comfortable leveraging ambiguous problem statements and appropriately applying AI tools alongside engineering judgment.
Capable of working on complex, real-world systems with a focus beyond typical feature shipping, contributing to core protocol stacks and critical infrastructure.