Design and implement AI-powered applications for enterprise batch processing, including LLM applications, intelligent agents, RAG solutions, prompt engineering, fine-tuning, guardrails, and model evaluation. Automate batch trigger and workflow configuration management, support migration to Google Cloud, improve platform scalability and reliability, and develop AI-assisted testing automation.
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Team Overview
The US Market Core Credit Batch Team is responsible for enabling and operating the batch processing capabilities for the US Credit business on the OneTru platform. The batch workload has already been migrated to OneTru and is currently running in production.• The team operates as a globally distributed organisation, with members located across both India and the United States, ensuring continuous support, platform evolution, and migration activities.
• The batch ecosystem processes petabytes of data annually, making it one of the most data-intensive platforms within the Credit domain. Daily operations include:
* Management of approximately 1,000 batch trigger configurations
* Execution and support of 100+ LFE (Logical Flow Engine) configurations
* Processing of large-scale credit and operational data workloads on a daily basis This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.
Role Overview And Core Responsibilities
- Accelerate migration from on-premises infrastructure to OneTru GCP cloud portal. Deliver a scalable and resilient batch processing platform capable of handling enterprise-scale data volumes.
- Simplify management of batch triggers and LFE daily running configurations through automation and standardisation using AI.
- Improve operational efficiency, reliability, and time-to-market for business initiatives.
- Testing automation using AI.
Required Knowledge And Experiences
- Design and implement AI-powered applications using Large Language Models (LLMs).
- Develop intelligent agents capable of planning, reasoning, tool usage, and workflow orchestration.
- Build Retrieval-Augmented Generation (RAG) solutions using structured and unstructured enterprise data.
- Evaluate, benchmark, and optimize LLMs for enterprise use cases.
- Implement prompt engineering, model fine-tuning strategies, and guardrails.
Required Technical Skills
- Large Language Models (LLMs)
- Prompt Engineering
- Retrieval Augmented Generation (RAG)
- Agentic AI Architectures
- Model Evaluation & Benchmarking
- Embedding Models
- Vector Databases
- Python (Expert)
- SQL
- REST APIs
- LangChain
- LangGraph
- Google Cloud Platform (Preferred)
TransUnion Overview:
At TransUnion, we encourage and are committed to creating a real, positive impact and shared sense of purpose within our Workforce for Good, which empowers our people to grow, innovate and contribute to a better future for our communities and customers. We strive to build an environment where our associates are in the driver’s seat of their professional development— while having access to help along the way. We recognize that success comes when our associates thrive both professionally and personally; that’s why we prioritize work/life flexibility and offer resources for our teams across the globe to collaborate and drive excellence.
Be a part of our Workforce for Good – you’ll work with great people, pioneering products and cutting-edge technology.
TransUnion Job Title
Engineer, Applications Development
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