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In-demand GenAI role, mid-level experience band, and metro hiring increase applicant competition.
GenAI and LLM engineering skills transfer across industries but require specialized ML/LLM expertise, so medium sensitivity.
Explicit 2–7 year requirement plus many mandatory GenAI/LLM frameworks and libraries enforces strict filtering.
Develop and deploy Generative AI applications utilizing Large Language Models (LLMs) and transformer-based architectures.
Design and integrate AI agents with external tools, APIs, databases, and enterprise services, focusing on Agentic AI concepts.
Implement features involving prompt engineering, Retrieval-Augmented Generation (RAG), semantic search, and AI application optimization.
2–7 years of hands-on experience in AI/ML, Generative AI, or related software development.
Strong programming skills in Python and experience with AI/ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
Hands-on experience with LLMs such as GPT, Azure Open AI, or similar open source/commercial models, and GenAI application frameworks like LangChain or LlamaIndex.
Experience developing REST APIs using FastAPI or similar frameworks.
Experienced in Agentic AI including AI agents, tool calling, planning, and multi-agent workflows.
Proficient with advanced AI development concepts such as prompt engineering, context management, and AI-assisted coding tools (e.g., GitHub Copilot).
Comfortable working within SDLC and Agile methodologies to deliver optimized, secure AI-generated solutions.