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Tier-1 brand, mid-level generalist GenAI role, metro location, and broad skill requirements increase applicant density.
GenAI and engineering skills are broadly transferable across industries, though enterprise integration adds some domain specifics.
Mandatory GenAI expertise, Python/cloud stacks, and explicit 3+ years requirement create strict filters.
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Design, develop, and deploy AI-powered applications and production-ready solutions focusing on Generative AI including LLMs, RAG architectures, and AI agents.
Build backend services, APIs, integrations, and user interfaces using frameworks like FastAPI, Flask, React, and Next.js, ensuring scalability and cost efficiency.
Collaborate with architects, engineers, and stakeholders to deliver enterprise-scale AI solutions while contributing to reusable frameworks and engineering best practices.
3+ years of work experience.
Strong proficiency in Python and experience with APIs using FastAPI or Flask.
Hands-on experience with Generative AI frameworks (e.g., LangChain, LangGraph) and cloud platforms (Azure, AWS, or GCP).
MBA degree mandatory.
Experienced in full lifecycle AI solution development from prototyping to production deployment in enterprise environments.
Deep understanding of Generative AI concepts including prompt engineering, vector databases, agentic AI, and use of leading AI platforms.
Skilled in cloud-native development practices with familiarity in containerization (Docker) and CI/CD pipelines.