AI Data Engineer - Rockerbox

Overview

Rockerbox is building the next generation of marketing intelligence, and we're looking for someone to help us build the AI systems everyone else just theorizes about. As a Staff AI Data Engineer, you'll research, design, and architect data systems purpose-built for AI agents, automations, and decisioning engines. You'll also apply data science and model-tuning techniques to optimize LLMs and solve complex marketing challenges for our clients.

If you enjoy turning high-volume data into clean, powerful systems-and you want your work to drive real business outcomes rather than just dashboards-this role puts you right at the center of the action.

• Apply bleeding edge AI theory to the design and implementation of large-scale data systems that feed AI agents and autonomous workflows.
• Use data science techniques to fine-tune, evaluate, and optimize LLMs for marketing-specific tasks: attribution insights, anomaly detection, summarization, classification, and automated recommendations.
• Build end-to-end automations using LLMs, internal data, and external signals to eliminate repetitive human tasks.
• Build AI-driven automations that reduce manual work across Rockerbox and unlock new client-facing capabilities.
• Design retrieval, orchestration, and memory layers that make our AI agents smarter over time.
• Establish best practices for AI data quality, observability, experiments, and safety.
• Lead R&D initiatives: rapid prototyping, experimentation, model evaluations, and productionization.
• Mentor data scientists and engineers across organization to raise the bar on LLM use company-wide.

• 8+ years of experience in data engineering, AI, ML platforms, or large-scale distributed systems.
• Hands-on experience integrating LLMs into production systems (OpenAI, fine-tuning, embeddings, RAG, vector stores, or custom agent orchestration).
• Strong understanding of experimentation, model evaluation, and performance tuning.
• You think in systems: storage, retrieval, metadata, reliability, latency, failure modes.
• Ability to work from ambiguity to execution - you're comfortable being the first to figure something out.
• Strong communication skills: you can explain tradeoffs, scope decisions, and technical strategy clearly.