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Niche Generative AI/agent framework requirements reduce applicant density despite mid-level experience.
Heavy LLM, RAG, agent, and vector DB expertise creates strong domain-specific hiring bias.
Multiple mandatory LLM, agentic framework, cloud, and 5–7 years requirements make filters highly strict.
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Design and develop scalable Generative AI applications and agentic AI solutions for enterprise use cases.
Build and orchestrate AI agents using frameworks such as LangChain, LangGraph, Google ADK, or similar technologies.
Integrate LLMs with enterprise systems and maintain backend services, APIs, microservices, and data pipelines powering AI-driven products.
5-7 years of experience in software engineering.
Strong proficiency in Python and experience developing production-ready applications with Generative AI and LLM technologies.
Hands-on experience with at least two agentic AI frameworks like LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility.
Experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, or Google Vertex AI/ADK.
Experienced in architecting AI solutions involving advanced AI patterns like RAG, Agentic RAG, tool/function calling, and human-in-the-loop workflows.
Skilled in backend development including REST/gRPC APIs, asynchronous programming, Docker, and frameworks like FastAPI or Flask.
Capable of working collaboratively across global teams with strong system design, problem-solving, and communication skills.