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Mid-level AI role in metro, broad fullstack+LLM requirements and known consultancy brand increase competition.
LLM, Python and cloud skills transfer easily, but enterprise consulting experience increases industry specificity.
Explicit 3–5 years plus mandatory LLM, Python, API, and cloud skills tighten candidate filters.
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Lead design, development, and deployment of enterprise-grade AI solutions including LLMs, advanced prompt engineering, and agentic AI systems.
Architect scalable REST and GraphQL APIs and drive backend development primarily using Python frameworks like FastAPI, Django, or Flask.
Mentor junior developers, establish CI/CD pipelines, and ensure security and production readiness in cloud-native AI platforms on Azure and AWS.
3–5 years of hands-on AI development experience focusing on LLMs and agentic AI systems.
Proficiency in Python backend frameworks (FastAPI, Django, Flask) and API design (REST, GraphQL).
Experience with front-end frameworks (React, Next.js, Vue.js) and additional backend languages like Node.js, Go, or Java (Spring Boot).
Knowledge of cloud platforms Azure, AWS and CI/CD practices using GitHub Actions.
Demonstrated ability to lead AI-related architectural designs and mentor junior team members.
Experience building AI copilots or workflow automation solutions and familiarity with low-code platforms like Power Apps and Copilot Studio.
Strong understanding of cloud-native architectures with security/compliance awareness and experience collaborating cross-functionally across full stack and cloud teams.