TransUnion's Job Applicant Privacy Notice
Team Overview
We are looking for a ML / LLM Application Engineer to join our AI team and build production ready applications powered by large language models (LLMs). 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
This role is focused on LLM application development, agent orchestration, and system integration, rather than deep ML research or training models from scratch. You will own end to end delivery of LLM driven features—from design and prototyping to deployment, monitoring, and optimization—working closely with product, platform, and data teams.
Responsibilities
- Design, build, and deploy LLM‑powered applications using LangChain, LangGraph, and related tooling.
- Maintain modular, scalable agent workflows for multi‑step reasoning, planning, and tool execution.
- Implement and own RAG pipelines, including data ingestion, chunking strategies, embedding workflows, and contextual retrieval.
- Develop effective prompting strategies, tool calling logic, memory handling, and guardrails to ensure reliable system behavior.
- Integrate LLM applications with vector databases to enable semantic search and contextual intelligence.
- Own production considerations such as latency, cost optimization, reliability, and observability.
- Collaborate with product, platform, and data teams to translate business requirements into robust AI solutions.
- Contribute to architectural decisions, engineering best practices, and reusable patterns for LLM‑based systems.
Required Knowledge And Experiences
Required Qualifications
- 2+ years of experience building production software, with a strong focus on AI‑powered or LLM‑based applications.
- Strong proficiency in Python for building APIs, backend services, AI workflows and maintaining ML pipelines and services.
- Solid understanding of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, and feature engineering.
- Hands‑on experience with at least one machine learning framework or library (e.g., scikit‑learn, PyTorch, TensorFlow).
- Hands‑on experience developing LLM applications using frameworks such as LangChain and/or LangGraph.
- Solid understanding of LLM and NLP fundamentals, including embeddings, transformers, vector similarity search, and prompt design.
- Practical experience implementing retrieval‑augmented generation (RAG) systems.
- Experience integrating vector databases (e.g., FAISS, Pinecone, Weaviate, or similar).
- Experience deploying and operating production systems, including Docker, REST APIs, and CI/CD pipelines.
- Strong problem‑solving skills and ability to independently own features while collaborating across teams.
Good to Have
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with distributed systems, async processing, or microservice architectures.
- Exposure to MLOps practices, including model evaluation, experiment tracking, monitoring, and rollback strategies.
- Experience handling largescale structured and unstructured data.
- Exposure to multimodal LLM applications (text + image, audio, or video).
Familiarity with lightweight model adaptation techniques (e.g., inference optimization, prompt tuning, LoRA) is a plus.
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
Analyst, Applications Development
Skills Required
- 2+ years of experience building production software, focused on AI-powered or LLM-based applications
- Strong proficiency in Python for APIs, backend services, AI workflows, and ML pipelines
- Understanding of supervised and unsupervised learning, model evaluation, and feature engineering
- Hands-on experience with scikit-learn, PyTorch, TensorFlow, or another machine learning framework
- Hands-on experience developing LLM applications with LangChain and/or LangGraph
- Understanding of embeddings, transformers, vector similarity search, and prompt design
- Practical experience implementing retrieval-augmented generation systems
- Experience integrating vector databases such as FAISS, Pinecone, or Weaviate
- Experience deploying and operating production systems using Docker, REST APIs, and CI/CD pipelines
- Strong problem-solving skills and ability to independently own features while collaborating across teams
- Experience with AWS, Azure, or Google Cloud
- Familiarity with distributed systems, asynchronous processing, or microservice architectures
- Exposure to MLOps practices including evaluation, experiment tracking, monitoring, and rollback strategies
- Experience handling large-scale structured and unstructured data
- Exposure to multimodal LLM applications involving text, images, audio, or video
- Familiarity with inference optimization, prompt tuning, or LoRA
What the Team is Saying
TransUnion Compensation & Benefits Highlights
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Healthcare Strength — Healthcare is described as comprehensive with day-one medical, dental and vision coverage, plus HSA/FSA options and expanded mental-health support via Spring Health. Feedback suggests coverage depth and immediate eligibility are notable strengths.
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Parental & Family Support — Family support includes paid parental leave with a gradual return, adoption and caregiver assistance, and backup care through a Care@Work membership. External recognition highlights inclusive offerings such as fertility support and bereavement provisions.
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Leave & Time Off Breadth — Time-off programs feature flexible time off, paid holidays, two global wellness days, and paid volunteer time. Feedback suggests these leave elements contribute meaningfully to work-life balance.
TransUnion Insights
What We Do
TransUnion is a global information and insights company that makes trust possible by ensuring that each consumer is reliably and safely represented in the marketplace. We do this by having an accurate and comprehensive picture of each person. This picture is grounded in our legacy as a credit reporting agency which enables us to tap into both credit and public record data; our data fusion methodology that helps us link, match and tap into the awesome combined power of that data; and our knowledgeable and passionate team, who stewards the information with expertise, and in accordance with local legislation around the world. Because of our work, organizations can better understand consumers in order to make more informed decisions, and earn their trust through great, personalized experiences, and the proactive extension of the right opportunities, tools and offers. In turn, consumers can be confident that their data identities will result in the opportunities they deserve. We make trust possible, so businesses and consumers can transact with confidence and achieve great things. We call this Information for Good®—it’s our purpose, and what drives us every day.
Why Work With Us
Our culture is welcoming, energetic and innovative. There’s an overall synergy that flows throughout TransUnion, creating a sense of unity in knowing that we’re all working to achieve the same overall goal. We’re dedicated to providing opportunities for our people to get involved and stay connected with their colleagues across the globe.
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Hybrid Workspace
Employees engage in a combination of remote and on-site work.
