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 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