AI Engineer – GenAI Platform, Mid-Level

Job not on LinkedIn

🕒 September 11

🤠 Texas – Remote

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⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

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👻 Ghost score 15%

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🗣️🇧🇷🇵🇹 Portuguese Required

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Logo of Experian

Experian

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

• Design and develop Generative AI services and multi-agent systems • Implement RAG, tool calling, and agent orchestration solutions • Integrate and operate models through LLM gateways • Develop LLMOps practices for monitoring, observability, and governance • Implement consumption measurement, chargeback, and inference cost optimization mechanisms • Build and maintain data pipelines for billing and metering • Apply MLOps, CI/CD, automated testing, and model lifecycle management practices • Respond to incidents and support monitoring, reliability, and continuous improvement of services • Collaborate with global Product, Engineering, Platform, Security, and Data teams

🎯 Requirements

• Experience in Software Engineering and Applied AI • Hands-on experience delivering GenAI projects in production environments • Advanced English proficiency • Knowledge of GenAI and Agentic AI • Knowledge of multi-agent orchestration, tool calling, and multi-step reasoning • Knowledge of RAG and prompt engineering • Experience with LangChain, LangGraph, or equivalent frameworks • Knowledge of LLMOps, LLM platforms, and LLM gateways such as LiteLLM or similar tools • Experience integrating models through APIs • Knowledge of observability and evaluation for LLM-based applications • Experience optimizing latency and performance • Knowledge of vector databases and retrieval mechanisms • Advanced Python skills • AWS experience preferred • Understanding of best practices in architecture, observability, and reproducibility • Knowledge of MLOps, version control, and experiment tracking • Experience with CI/CD, automated testing, and deployment and rollback of AI services • Knowledge of batch and streaming data pipelines • Experience with Spark and Lakehouse architectures • Knowledge of data orchestration • Nice to have: Kafka and event streaming; Terraform and Infrastructure as Code; Databricks, including Delta Lake and DLT; internal developer platforms; experience working in global and distributed environments

🏖️ Benefits

• Inclusive recruitment and professional development initiatives • Affinity groups supporting underrepresented groups: ExperianPride, Ubuntu, Women in Experian, Aspire, and Connecting Generations

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