Senior AI Workflow & Systems Engineer

⚡ Senior AI Workflow & Systems Engineer Build and run the AI infrastructure that powers every team at TubeScience .

🗃️ Role: Senior AI Workflow & Systems Engineer 📍 Location: Remote (Los Angeles based preferred) 💰 Compensation: Remote $70,000–$120,000 | Los Angeles $110,000–$160,000 👤 Reports to: VP of IS

🏢 Team: Information Systems

🚀 About TubeScience

TubeScience is a data-driven creative studio producing performance advertising at massive scale — and we're growing fast. We're looking for a Senior AI Workflow & Systems Engineer to be the most technically sophisticated AI builder in the company. You'll sit in IT but serve everyone — owning the infrastructure, deployments, and systems that make our AI initiatives real, and unblocking every team that's building on top of them.

💡 The Role

This is a systems and deployment role for someone genuinely excited about where AI is taking enterprise engineering. You won't just design workflows — you'll own the infrastructure they run on, keep them running reliably, and be the expert other teams call when things break or they hit a wall.

You are the architect, the deployer, the maintainer, and the unlocker — all in one. When there's no PM driving an AI initiative, you'll step in and own it end-to-end.

🎬 What You'll Own

🤖 AI Workflow Engineering

• Build and deploy LLM-powered applications and agent-based workflows that eliminate manual effort across the company - Design multi-step agentic pipelines — tool use, RAG, structured outputs — built for production, not demos - Integrate AI workflows with TubeScience 's existing systems via REST APIs, webhooks, and custom integrations

- Develop automation pipelines

• Evaluate emerging AI tooling and own build-vs-buy decisions

🏗️ Infrastructure & Deployment

• Own deployment and management of AI workflows and applications on Vercel and cloud platforms - Build and maintain the infrastructure that supports TubeScience 's AI initiatives — including cloud-based agents, serverless functions, and supporting services - Design for resilience: logging, error handling, alerting, and monitoring across all deployed systems - Manage secrets, environment configs, and deployment pipelines across environments - Align with engineering on architecture, scalability, and infrastructure decisions

🤝 Cross-Functional Enablement

• Serve as the go-to technical resource for teams across TubeScience building AI-powered workflows and apps - Deploy, maintain, and improve departmental AI tools — owning the full lifecycle from build to production - Debug and unstick builders across the company when they hit technical walls - Translate team-specific business needs into precise technical requirements and actionable solutions - Serve as final e