Staff AI Data Engineer - Rockerbox

DoubleVerify is seeking a Staff AI Data Engineer to help build the next generation of marketing intelligence at Rockerbox. The role involves researching, designing, and architecting data systems for AI agents and automations, as well as applying data science techniques to optimize large language models for complex marketing challenges.

Responsibilities:

• 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

Requirements:

• 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