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Mid-level experience, metro location, broad fullstack-plus-AI skills create high competition density.
Core LLM and ML engineering skills are transferable, but enterprise copilot and low-code specifics raise domain specificity.
Explicit 3–5 years plus mandatory LLM, cloud, and backend tech stack increases shortlisting strictness.
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Lead design and development of enterprise-grade AI solutions focusing on LLMs, agentic AI, and advanced prompt engineering.
Architect scalable AI platforms with REST and GraphQL APIs and backend development primarily in Python using FastAPI, Django, or Flask.
Mentor junior developers, collaborate with frontend teams, and ensure production readiness including security compliance and CI/CD pipelines on cloud platforms (Azure, AWS).
3-5 years of hands-on AI development experience in building and deploying AI solutions.
Proficiency in Python backend frameworks (FastAPI, Django, Flask) and working knowledge of Node.js, Go, or Java (Spring Boot).
Experience with LLMs, agentic AI systems, REST and GraphQL APIs, and front-end frameworks (React, Next.js, Vue.js).
Familiarity with cloud platforms (Azure, AWS), code management using Git, and CI/CD pipelines via GitHub Actions.
Proven ability to design scalable AI architecture and lead technical efforts in AI platform development.
Experience mentoring or guiding junior developers and collaborating across frontend and backend teams.
Background in cloud-native architectures with an understanding of security and production readiness in enterprise environments.