Sr. Software Engineer II - AI Rockerbox
AI summary of the role
Senior AI engineer role on the Rockerbox team (DoubleVerify's outcome measurement product) to design and build AI systems for agents, automations, and decisioning engines.
What you’ll do
- Identify and prioritize AI opportunities with engineers, PMs, and data teams
- Translate product requirements into AI-driven client-facing solutions
- Build end-to-end LLM automations using internal and external data
- Design agentic workflows and orchestration pipelines for complex processes
What you’ll bring
- 6+ years in software/data engineering or large-scale distributed systems
- Hands-on LLM integration in production (embeddings, RAG, vector stores, agent orchestration)
- Strong Python and SQL
- Kubernetes and container-based deployment
Technologies
LLM · RAG · vector stores · agent orchestration · Python · SQL · Kubernetes · embeddings · agentic workflows · observability
About DoubleVerify
Independent third-party platform that verifies, optimizes, and proves digital ad quality (fraud, viewability, brand safety, attribution) for the world's largest brands, agencies, and ad platforms.
Public · 1000–2000 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
Location: Remote (US) Team: Engineering – AI & Data Systems 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
More from the job description
Location: Remote (US) Team: Engineering – AI & Data Systems 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. What You Bring 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.
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