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Remote, broad AI full-stack remit and generalist title increase applicant density.
Demands AI-native engineering and domain compliance expertise, limiting cross-industry transferability.
Requires specialized LLM, RAG, governance and HIPAA skills, creating strict technical and compliance filters.
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Identify and translate ambiguous, high-value business problems into AI solutions by engaging with stakeholders and mapping end-to-end processes.
Design, develop, and iterate full-stack AI prototypes rapidly, managing technical architecture from prompt design to user interface using Claude and related AI tools.
Ensure AI solutions comply with governance standards and scale to production with documentation and collaboration with AI Governance teams.
Experience Required: Not explicitly mentioned in the JD.
Must have skills in AI development, including LLM orchestration, retrieval-augmented generation (RAG), REST API integration, and front-end interface development.
Familiarity with responsible AI principles, including bias review, explainability, HIPAA compliance, audit logging, and model monitoring.
Ability to work closely with business stakeholders, communicate technical concepts to non-technical leaders, and participate in business rhythm meetings.
Operates at the intersection of AI engineering and business stakeholder engagement, capable of problem discovery and solution scoping at enterprise level.
Experienced in rapid prototyping and evolving AI solutions from pilot to scalable production-grade systems with compliance focus.
Has domain depth in regulated industries like healthcare, able to develop expertise in client operations, data, and competitive pressures to guide AI strategy.