AI Engineer – GenAI Platform, Mid-Level

This is a fully remote position, open to applicants in Texas.

📋 Description

• Create and design Generative AI services and multi-agent systems.

• Execute RAG, tool calling, and agent orchestration solutions.

• Integrate and operate models via LLM gateways.

• Establish LLMOps practices for monitoring, observability, and governance.

• Implement mechanisms for consumption measurement, chargeback, and inference cost optimization.

• Construct and manage data pipelines for billing and metering purposes.

• Utilize MLOps, CI/CD, automated testing, and model lifecycle management practices.

• Address incidents and support the monitoring, reliability, and continuous enhancement of services.

• Collaborate with global teams across Product, Engineering, Platform, Security, and Data.

⛳️ Requirements

• Proven experience in Software Engineering and Applied AI.

• Practical experience delivering GenAI projects within production settings.

• Proficient in English at an advanced level.

• Familiarity with GenAI and Agentic AI concepts.

• Understanding of multi-agent orchestration, tool calling, and multi-step reasoning.

• Knowledge of RAG and prompt engineering techniques.

• Experience with LangChain, LangGraph, or similar frameworks.

• Awareness of LLMOps, LLM platforms, and LLM gateways like LiteLLM or comparable tools.

• Background in integrating models through APIs.

• Knowledge of observability and evaluation methods for LLM-based applications.

• Experience in optimizing latency and performance.

• Familiarity with vector databases and retrieval techniques.

• Advanced proficiency in Python.

• Experience with AWS is preferred.

• Understanding of best practices in architecture, observability, and reproducibility.

• Knowledge of MLOps, version control, and experiment tracking practices.

• Experience with CI/CD, automated testing, and deployment and rollback of AI services.

• Familiarity with batch and streaming data pipelines.

• Experience with Spark and Lakehouse architectures.

• Understanding of data orchestration.

• Nice to have: Experience with Kafka and event streaming; Terraform and Infrastructure as Code; Databricks, including Delta Lake and DLT; internal developer platforms; and working in global and distributed environments.

🏝️ Benefits

• Commitment to inclusive recruitment and professional development initiatives.

• Affinity groups that support underrepresented communities: ExperianPride, Ubuntu, Women in Experian, Aspire, and Connecting Generations.