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Mid-level experience band and popular GenAI title balanced by niche LLM tooling, yielding moderate competition.
Core LLM and ML skills transfer across industries, though enterprise integrations increase role specificity.
Many mandatory GenAI skills and explicit 2–7 years requirement make screening highly strict.
Develop and maintain Generative AI applications leveraging LLMs and frameworks like LangChain or LlamaIndex.
Design, implement, and integrate AI agents with external tools, APIs, databases, and enterprise services.
Optimize AI applications including prompt engineering, response quality evaluation, and AI-generated code validation and security.
2–7 years of hands-on experience in AI/ML, Generative AI, or related software development.
Strong programming skills in Python.
Experience with LLMs (e.g., GPT, Azure Open AI) and Generative AI frameworks such as LangChain, LangGraph, or LlamaIndex.
Experience developing REST APIs using FastAPI or similar frameworks.
Familiar with advanced Agentic AI concepts including multi-agent workflows, tool calling, and reasoning.
Experienced in Retrieval-Augmented Generation (RAG), embeddings, semantic search, and document-based Q&A.
Proficient in ML libraries (PyTorch, TensorFlow, Scikit-learn) and skilled in prompt engineering and AI-assisted development workflows.