Senior AI Workflow & Systems Engineer

<p>⚡ Senior AI Workflow &amp; Systems Engineer &nbsp;<br>Build and run the AI infrastructure that powers every team at TubeScience.</p> <p>🗃️ Role: Senior AI Workflow &amp; Systems Engineer &nbsp;<br>📍 Location: Remote (Los Angeles based preferred) &nbsp;<br>💰 Compensation: Remote $70,000–$120,000 | Los Angeles $110,000–$160,000 &nbsp;<br>👤 Reports to: VP of IS &nbsp;<br>🏢 Team: Information Systems</p> <p>🚀 About TubeScience</p> <p>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 &amp; 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.</p> <p>💡 The Role</p> <p>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.</p> <p>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.</p> <p>🎬 What You'll Own</p> <p>🤖 AI Workflow Engineering<br>- Build and deploy LLM-powered applications and agent-based workflows that eliminate manual effort across the company<br>- Design multi-step agentic pipelines — tool use, RAG, structured outputs — built for production, not demos<br>- Integrate AI workflows with TubeScience's existing systems via REST APIs, webhooks, and custom integrations<br>- Develop automation pipelines<br>- Evaluate emerging AI tooling and own build-vs-buy decisions</p> <p>🏗️ Infrastructure &amp; Deployment<br>- Own deployment and management of AI workflows and applications on Vercel and cloud platforms<br>- Build and maintain the infrastructure that supports TubeScience's AI initiatives — including cloud-based agents, serverless functions, and supporting services<br>- Design for resilience: logging, error handling, alerting, and monitoring across all deployed systems<br>- Manage secrets, environment configs, and deployment pipelines across environments<br>- Align with engineering on architecture, scalability, and infrastructure decisions</p> <p>🤝 Cross-Functional Enablement<br>- Serve as the go-to technical resource for teams across TubeScience building AI-powered workflows and apps<br>- Deploy, maintain, and improve departmental AI tools — owning the full lifecycle from build to production<br>- Debug and unstick builders across the company when they hit technical walls<br>- Translate team-specific business needs into precise technical requirements and actionable solutions<br>- Serve as final escalation for complex AI and systems issues teams can't resolve on their own</p> <p>🔬 Ownership &amp; Improvement<br>- Proactively audit AI systems and workflows for reliability issues, inefficiencies, and improvement opportunities<br>- When there's no dedicated PM on an AI initiative, step in: define the problem, scope the solution, and drive it to completion<br>- Prototype emerging AI tools and frameworks and bring the best ones into TubeScience's stack<br>- Document every system thoroughly so the company can run it confidently</p> <p>🧬 What We're Looking For</p> <p>Background &amp; Experience<br>- 4–6+ years in software engineering, DevOps, or systems engineering — with hands-on AI/ML experience<br>- Strong foundation as a software, systems, or DevOps engineer who has grown into AI — not the other way around<br>- Proven experience deploying and managing production applications on Vercel, AWS, GCP, or equivalent<br>- Hands-on with LLMs, generative AI, and orchestration tools (n8n, Make, Zapier, LangChain, or equivalent)<br>- Proven REST API integration experience with solid edge-case handling<br>- Experience building or maintaining cloud-based agents and serverless infrastructure</p> <p>Technical Skills<br>- Strong Python and/or JavaScript/Node.js — clean, production-grade code<br>- Solid understanding of deployment pipelines, CI/CD, environment management, and secrets handling<br>- Experience with vector databases and embedding-based retrieval<br>- Comfortable with cloud infrastructure (AWS and/or GCP) and cloud-native application patterns<br>- Familiarity with monitoring, logging, and alerting for production systems</p> <p>Soft Skills<br>- Highly autonomous — identifies problems and ships solutions without waiting to be asked<br>- Effective communicator across technical and non-technical audiences<br>- Strong product instincts: can step into ownership of an initiative when there's no PM in the room<br>- Calm under pressure; reliable when other teams are blocked and need answers fast<br>- Comfortable working across many different teams and problem domains simultaneously</p> <p>➕ Bonus Points<br>- Experience with AI agent frameworks<br>- Background in high-volume performance advertising, media, or creative production<br>- Experience with AI in a production context<br>- Multi-step agentic pipeline design or large-scale workflow orchestration<br>- Experience with data pipelines or BI tooling</p> <p>✨ Benefits<br>🩺 Health, Vision &amp; Dental coverage &nbsp;<br>🧳 Unlimited PTO &nbsp;<br>💰 401(k) + Matching &nbsp;<br>💗 Life Insurance &nbsp;<br>🤒 Paid Sick Days &nbsp;<br>👶 Paid Parental Leav</p>