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Remote, high-demand GenAI domain but senior specialized profile limits applicant pool.
High — requires deep LLM, GenAI architecture, and enterprise governance expertise, limiting cross-industry transfers.
High — explicit 9+ years, mandatory GenAI architecture, cloud, security, and leadership requirements.
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Own architecture and technical vision for AI-powered user-facing applications involving Python, React, Generative AI, backend platforms for LLM inference, RAG systems, and AI workflows.
Lead design and implementation of scalable, secure, cost-efficient AI infrastructure including frontend AI-native UX, backend AI pipelines, and GenAI platform components.
Drive engineering standards, best practices, technical strategy, and influence architecture across teams, ensuring enterprise readiness (security, privacy, governance) and collaboration with cross-functional leaders.
9+ years total software engineering experience.
Proven experience architecting and delivering production-grade Generative AI applications at scale.
Strong technical skills in Python, system design (backend, frontend, AI infrastructure), cloud platforms (AWS, Azure, or GCP), and knowledge of LLM integration patterns, RAG systems, AI-driven UX design.
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
Demonstrated ability to translate ambiguous business problems into durable technical architectures and lead cross-team technical influence.
Experience with enterprise AI considerations including security, privacy, compliance, governance, and responsible AI practices.
Strong communication skills with ability to influence senior leadership and partner effectively across product, design, data, and business domains.