Senior AI Workflow & Systems Engineer

TubeScience
Los Angeles, CA, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Compensation
$110,000.0 - $160,000.0
Working hours
Regular working hours
Job source

Tech stack

JavaScript (Programming Language) Artificial Intelligence Amazon Web Services Systems Engineering Cloud Computing Encodings Continuous Integration Software Debugging DevOps Python (Programming Language) Next.js Software Engineering
+15 more
Data Logging Business Intelligence Development Studio Google Cloud Delivery Pipeline Large Language Models Zapier Build Management Production Code Enterprise Integration Virtual Agents Restful APIs Webhooks Data Pipelines Automation Anywhere Serverless Computing

Job description

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

ļø 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

Requirements

Do you have experience in Zapier?, 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 & conditions

1.91.9 out of 5 stars Los Angeles, CA Remote $110,000 - $160,000 a year, Pulled from the full job description

  • Parental leave
  • Health insurance
  • 401(k) matching
  • Vision insurance
  • Dental insurance
  • Paid sick time
  • Life insurance, Health, Vision & Dental coverage Unlimited PTO 401(k) + Matching Life Insurance Paid Sick Days Paid Parental Leav

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