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About the role
Required Skills: Build GenAI applications leveraging foundation models and advanced architectures such as GraphRAG. Develop autonomous AI agents using modern agentic frameworks. Design and deploy RAG and GenAI services using Python (FastAPI), Docker, and cloud platforms (AWS, Azure, or GCP). Build scalable REST APIs that power LLM-driven applications integrated with enterprise data sources. Implement LLM evaluation frameworks using tools such as Ragas, LangSmith, or custom benchmarks to measure answer relevance, groundedness, and hallucination rates. Apply LLMOps/MLOps practices, including CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and response quality. Develop systems leveraging embeddings at scale, knowledge graphs, and ontology extraction. Collaborate across engineering teams, mentor developers, and help drive innovation in GraphRAG and agentic AI architectures.
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