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Mid-level, popular GenAI role with broad skillset requirements increases candidate competition.
Highly specialized GenAI, LLM, and vector/RAG skills limit cross-industry transferability.
Explicit 2–7 year requirement plus many mandatory GenAI frameworks and libraries creates strict filters.
Develop and implement Generative AI applications leveraging Large Language Models (LLMs) and frameworks such as LangChain or LlamaIndex.
Design and build AI agents integrating external tools, APIs, databases, and enterprise services with capabilities like planning, reasoning, memory, and multi-agent workflows.
Optimize AI application performance including prompt engineering, hallucination detection, model evaluation, and secure, efficient AI-generated code development.
2 to 7 years of experience in AI/ML or Generative AI software development.
Strong programming skills in Python and familiarity with AI/ML frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn.
Hands-on experience with LLMs (e.g., GPT, Azure Open AI) and relevant GenAI development frameworks (e.g., LangChain, LlamaIndex).
Experience in developing REST APIs using frameworks like FastAPI.
Technical background focused on Generative AI with practical experience in building and deploying AI agents and applications.
Experienced in advanced AI concepts including Agentic AI, Retrieval-Augmented Generation, prompt engineering, and AI-assisted development workflows.
Operates effectively within Agile and SDLC environments, capable of validating and optimizing AI-generated code and ensuring application performance.