Artificial Intelligence Engineer

We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position.

Required Skills & Experience

What You'll Do

• Design and build AI and machine learning solutions with a strong focus on production-ready applications.
• Develop LLM-powered applications, RAG systems, and AI agents.
• Build agentic AI workflows using LangGraph.
• Build automation around AI and ML workflows.
• Develop and deploy AI solutions in the cloud, primarily using GCP and Vertex AI.
• Develop evaluations, testing frameworks, and monitoring to measure the quality and performance of AI solutions.
• Leverage Langfuse for observability and evaluation of LLM applications.
• Work across traditional machine learning, generative AI, and reinforcement learning use cases.
• Support the end-to-end AI lifecycle, including development, deployment, evaluation, testing, and monitoring.

What We're Looking For

• 3-5 years of experience in machine learning, AI engineering, software engineering, or a related field.
• Hands-on experience building LLM applications and AI agents.
• Experience designing and implementing Retrieval-Augmented Generation (RAG) systems.
• Experience with LangGraph or similar agent orchestration frameworks.
• Experience building AI/ML solutions on GCP, particularly Vertex AI. AWS experience is also relevant.
• Understanding of LLM evaluation, observability, testing, and monitoring, ideally including experience with Langfuse.
• Experience deploying AI/ML solutions into production.
• Exposure to traditional ML and reinforcement learning is an asset.
• Ability to think beyond the model itself and build reliable, scalable AI products.

Job Description

Insight Global is looking for an AI Engineer to help build and scale AI-powered solutions supporting media insights, advertising campaigns, data analytics, and business intelligence.

This individual will be responsible for taking AI solutions from concept through production, including building LLM applications, RAG systems and AI agents, deploying solutions in the cloud, and developing the evaluation and monitoring frameworks needed to ensure those solutions perform effectively.