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Metro location, popular AI role, broad GenAI skill requirements increase applicant competition.
Role requires specialized AI architecture and production GenAI experience, limiting cross-industry transferability.
Explicit 8–12 years and mandatory GenAI architecture, LLM, and production delivery experience make filters stringent.
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Own end-to-end delivery of AI use-cases from problem framing through MVP to production and UAT.
Lead rapid prototyping and design of enterprise-grade GenAI solutions including RAG, agentic workflows, and human-in-the-loop systems.
Manage concurrent deliveries with 4–6 week MVP timelines and mentor engineering teams (10-15 members) ensuring architecture consistency and delivery velocity.
8–12 years of experience in AI solution architecture or applied AI delivery.
Proven experience delivering AI/GenAI solutions from concept to production.
Strong technical skills in LLM ecosystems, embeddings, vector databases, agent frameworks, cloud AI services, and software engineering fundamentals including CI/CD and automation.
Ability to implement data privacy, governance controls and familiarity with Agile methodologies and tools like JIRA.
Experienced in managing multiple AI project deliveries on tight deadlines within a structured enterprise environment.
Skilled at bridging business and technology to translate complex business problems into structured AI solutions.
Comfortable leading medium-sized engineering teams and interfacing directly with stakeholders to articulate trade-offs and value realization.