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Well-known firm, mid-level sought skills, and common title create medium applicant competition.
LLM and graph skills are transferable, but domain-specific agentic AI and BU context raise sensitivity to medium.
Mandatory 5+ years and specific LLM, graph, and cloud skills make shortlisting highly selective.
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Own and lead domain-specific model evaluation, fine-tuning, and operationalization within the Agentic AI platform initiative.
Design and implement evaluation frameworks and scalable AI components such as knowledge graphs, embeddings, and inference engines.
Collaborate across engineering, product, and business to deploy production-scale AI solutions and deliver value through agentic AI workflows.
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
Minimum 5 years overall IT experience with at least 3 years in applied machine learning or NLP, including production environments.
Strong experience with LLMs, generative AI, NLP fine-tuning and evaluation, plus proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn).
Experience with graph databases (Neo4j, DGL), knowledge graphs, vector stores, cloud AI/ML services (AWS, Azure, GCP), and MLOps practices.
Experienced in leading applied research and product-oriented AI/ML initiatives focused on large language models and advanced reasoning techniques.
Hands-on technical capability in production-scale deployments, evaluation metric design, and cross-functional collaboration.
Familiar with agentic AI systems or related cutting-edge generative AI technologies and workflows.