Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Strong employer brand, metro location, and popular Data Scientist title increase candidate competition.
Generative AI and LLM engineering skills transfer across industries, so background fit is broadly flexible.
Explicit master's degree and minimum experience plus technical deployment expectations create strict screening filters.
Develop and deploy agentic AI systems and solutions using cloud-native services for complex enterprise use cases.
Design and optimize retrieval-augmented generation (RAG) pipelines and prompt engineering strategies to enhance LLM-powered applications.
Collaborate cross-functionally to translate business requirements into technical implementations, monitor performance metrics, and communicate technical insights to stakeholders.
Bachelor's and Master's degrees are mandatory.
Minimum 2 years of relevant work experience.
Proficiency in English (oral and written) is required.
Experience with Python development and cloud platforms (AWS, Azure, or GCP) is implied but not explicitly stated as mandatory for entry.
Demonstrated experience in building and deploying production-grade Agentic AI solutions using frameworks like LangChain, LangGraph, CrewAI, or AutoGen.
Strong knowledge of AI interoperability protocols (MCP, A2A) and advanced RAG architectures including Graph, Vectorless, and Hybrid RAG.
Hands-on experience with traditional AI/ML fundamentals (model building, fine-tuning, quantization) and awareness of Responsible AI and security practices.