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Specialized LLM/agent requirements lower applicant density, but strong TransUnion brand and metro location increase competition.
Role requires specialized LLM, RAG, and agent engineering skills, reducing industry transferability.
Mandatory expert LLM, LangChain, Python, and GCP skills create strict technical filters.
Lead migration of batch processing workloads from on-premises to OneTru GCP cloud platform for US Credit business.
Develop and maintain scalable, resilient batch processing systems handling petabytes of data and 1000+ batch triggers daily.
Automate and standardize batch trigger and LFE configuration management using AI to improve efficiency, reliability, and speed of business initiatives.
Proven experience designing and implementing AI-powered applications using Large Language Models (LLMs).
Proficiency in Python and SQL; experience with REST APIs, LangChain, LangGraph, and Google Cloud Platform preferred.
Experience with Retrieval-Augmented Generation (RAG), prompt engineering, LLM model fine-tuning, evaluation and benchmarking.
Work Experience Required: Not explicitly mentioned in the JD; role requires hybrid work with minimum two days per week onsite at a TransUnion office in India.
Experienced AI engineer with strong background in LLMs, RAG, and agentic AI architectures applicable to enterprise-scale data processing.
Comfortable working in a globally distributed team supporting continuous platform operations and migrations.
Demonstrates ability to design scalable AI-driven automation solutions improving operational processes in data-intensive batch environments.