Principal Engineer, AI

Job not on LinkedIn

🕒 July 31

🇧🇷 Brazil – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Experian

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1996

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Experian is a global leader in digital experience, technology, and transformation. They partner with recognized brands to enhance customer understanding, innovate product strategies, and implement agile technology solutions. With a focus on delivering superior customer experiences through AI, cloud architecture, and project management, Experian helps businesses streamline their operations and achieve their objectives effectively.

📋 Description

• Lead the technical direction of Generative AI projects and intelligent solutions • Design architectures for applications based on LLMs, RAG, and AI agents • Develop Java applications integrated with AI and Machine Learning services • Collaborate with Architecture, Product, Data, and Engineering teams to evolve solutions • Evaluate new technologies, frameworks, and AI models • Define development standards for AI-based applications • Ensure security, governance, scalability, and observability of intelligent solutions • Provide technical support to other engineers adopting AI within products • Build proofs of concept (POCs) for new AI capabilities

🎯 Requirements

• Software Engineering background • Strong experience with Java 17+ • Spring Boot • Microservices • REST APIs • GraphQL • Automated testing (JUnit, Mockito) • Design Patterns • SOLID principles • Clean Architecture • Domain-Driven Design (DDD) • Event-Driven Architecture • CI/CD (Jenkins, GitHub Actions) • Docker • Kubernetes • Practical experience with Generative AI • Large Language Models (LLMs) • Prompt Engineering • Retrieval-Augmented Generation (RAG) • AI Agents • MCP (Model Context Protocol) • OpenAI API, Azure OpenAI, or Amazon Bedrock • LangChain, LangGraph, or similar frameworks • Embeddings and vector databases (Pinecone, OpenSearch, pgvector, Weaviate, ChromaDB) • Fine-tuning and model evaluation (where applicable) • Knowledge of Responsible AI, governance, and AI security • Model evaluation, metrics, and cost/performance optimization

🏖️ Benefits

• Health coverage • Wellness programs • Flexible working hours • Professional development opportunities • Remote work