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# Sr. Software Engineer II - AI Rockerbox

- **Company:** DoubleVerify
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Information Engineering, Distributed Systems, Python (Programming Language), Software Engineering, SQL Databases, Large Language Models, Multi-Agent Systems, Kubernetes, Low Latency
- **Published:** September 14, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pjrc1tx6mb

## About the Role

* 6+ years of experience in software engineering, data engineering, or large-scale distributed systems.
 * Hands-on experience integrating LLMs into production systems (embeddings, RAG, vector stores, or agent orchestration).
 * Strong proficiency in Python and SQL.
 * Experience with Kubernetes and container-based infrastructure and deployment.
 * 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.

## Description

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 Sr. Software Engineer II in AI, you'll design and build systems purpose-built for AI agents, automations, and decisioning engines that drive real outcomes for our clients and internal teams. 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.

What You'll Do

 * Work closely with engineers, product managers, and data teams to identify and prioritize AI opportunities across the organization.
 * Translate product requirements into AI-driven solutions that directly impact the client experience.
 * Build end-to-end automations using LLMs, internal data, and external signals to eliminate repetitive tasks and unlock new client-facing capabilities.
 * Design and implement agentic workflows and orchestration pipelines that automate complex, multi-step processes.
 * Design retrieval, orchestration, and memory layers that make our AI agents smarter over time.
 * Establish best practices for AI data quality, observability, and safety.


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