⚡ 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 escalation for complex AI and systems issues teams can't resolve on their own
🔬 Ownership & Improvement
- Proactively audit AI systems and workflows for reliability issues, inefficiencies, and improvement opportunities
- When there's no dedicated PM on an AI initiative, step in: define the problem, scope the solution, and drive it to completion
- Prototype emerging AI tools and frameworks and bring the best ones into TubeScience's stack
- Document every system thoroughly so the company can run it confidently
🧬 What We're Looking For
Background & Experience
- 4–6+ years in software engineering, DevOps, or systems engineering — with hands-on AI/ML experience
- Strong foundation as a software, systems, or DevOps engineer who has grown into AI — not the other way around
- Proven experience deploying and managing production applications on Vercel, AWS, GCP, or equivalent
- Hands-on with LLMs, generative AI, and orchestration tools (n8n, Make, Zapier, LangChain, or equivalent)
- Proven REST API integration experience with solid edge-case handling
- Experience building or maintaining cloud-based agents and serverless infrastructure
Technical Skills
- Strong Python and/or JavaScript/Node.js — clean, production-grade code
- Solid understanding of deployment pipelines, CI/CD, environment management, and secrets handling
- Experience with vector databases and embedding-based retrieval
- Comfortable with cloud infrastructure (AWS and/or GCP) and cloud-native application patterns
- Familiarity with monitoring, logging, and alerting for production systems
Soft Skills
- Highly autonomous — identifies problems and ships solutions without waiting to be asked
- Effective communicator across technical and non-technical audiences
- Strong product instincts: can step into ownership of an initiative when there's no PM in the room
- Calm under pressure; reliable when other teams are blocked and need answers fast
- Comfortable working across many different teams and problem domains simultaneously
➕ Bonus Points
- Experience with AI agent frameworks
- Background in high-volume performance advertising, media, or creative production
- Experience with AI in a production context
- Multi-step agentic pipeline design or large-scale workflow orchestration
- Experience with data pipelines or BI tooling
✨ Benefits
🩺 Health, Vision & Dental coverage
🧳 Unlimited PTO
💰 401(k) + Matching
💗 Life Insurance
🤒 Paid Sick Days
👶 Paid Parental Leav
Skills Required
- 4-6+ years in software engineering, DevOps, or systems engineering with hands-on AI/ML experience
- Proven experience deploying and managing production applications on Vercel, AWS, or GCP
- Hands-on experience with LLMs, generative AI, and orchestration tools (n8n, Make, Zapier, LangChain, or equivalent)
- Proven REST API integration experience with solid edge-case handling
- Experience building or maintaining cloud-based agents and serverless infrastructure
- Strong Python and/or JavaScript/Node.js with production-grade coding practices
- Solid understanding of deployment pipelines, CI/CD, environment management, and secrets handling
- Experience with vector databases and embedding-based retrieval
- Comfortable with cloud infrastructure and cloud-native application patterns (AWS and/or GCP)
- Familiarity with monitoring, logging, and alerting for production systems
- Experience with AI agent frameworks (bonus)
- Background in high-volume performance advertising, media, or creative production (bonus)
- Experience with AI in a production context (bonus)
- Multi-step agentic pipeline design or large-scale workflow orchestration (bonus)
- Experience with data pipelines or BI tooling (bonus)
What We Do
As one of the fastest growing startups in Los Angeles, we're revolutionizing the way in which companies approach successful video advertising. Our team of award-winning Producers, Editors, Directors, Engineers, and Performance Marketing Managers are building a global studio where we can conceptualize, shoot, and produce hundreds of videos per day. Unlike traditional advertising agencies that pitch creative concepts for companies, hope they will perform, and outsource filming, we design videos that are guaranteed to convert. We use data to guide our creative process and leverage testing and analysis to make adjustments to react to users in real-time. What's atypical about the company: We're fast and data-driven: our teams develop concepts in the morning, shoot/edit in the afternoon, launch in the evening, and iterate the next day based on real-world performance. We’re a behavioral R&D lab at the core: We put 2,000+ video experiments per week, watched by tens of millions of people per day, that give us deep insights into how people make decisions. Over the past couple years, we’ve built an enormous library of IP around human behavior and visual communication. We work on a pure pay for performance basis. Zero production fees for video. Clients only pay us if our videos outperform anything they’re running internally.
