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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

B

uild and deploy LLM-powered applications and agent-based workflows that eliminate manual effort across the company

D

esign multi-step agentic pipelines - tool use, RAG, structured outputs - built for production, not demos

I

ntegrate AI workflows with TubeScience's existing systems via REST APIs, webhooks, and custom integrations

D

evelop automation pipelines

E

valuate emerging AI tooling and own build-vs-buy decisions

Infrastructure & Deployment

O

wn deployment and management of AI workflows and applications on Vercel and cloud platforms

B

uild and maintain the infrastructure that supports TubeScience's AI initiatives - including cloud-based agents, serverless functions, and supporting services

D

esign for resilience: logging, error handling, alerting, and monitoring across all deployed systems

M

anage secrets, environment configs, and deployment pipelines across environments

A

lign with engineering on architecture, scalability, and infrastructure decisions

Cross-Functional Enablement

S

erve as the go-to technical resource for teams across TubeScience building AI-powered workflows and apps

D

eploy, maintain, and improve departmental AI tools - owning the full lifecycle from build to production

D

ebug and unstick builders across the company when they hit technical walls

T

ranslate team-specific business needs into precise technical requirements and actionable solutions

S

erve as final escalation for complex AI and systems issues teams can't resolve on their own

Ownership & Improvement

P

roactively audit AI systems and workflows for reliability issues, inefficiencies, and improvement opportunities

W

hen there's no dedicated PM on an AI initiative, step in: define the problem, scope the solution, and drive it to completion

P

rototype emerging AI tools and frameworks and bring the best ones into TubeScience's stack

D

ocument 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

S

trong foundation as a software, systems, or DevOps engineer who has grown into AI - not the other way around

P

roven experience deploying and managing production applications on Vercel, AWS, GCP, or equivalent

H

ands-on with LLMs, generative AI, and orchestration tools (n8n, Make, Zapier, LangChain, or equivalent)

P

roven REST API integration experience with solid edge-case handling

E

xperience building or maintaining cloud-based agents and serverless infrastructure

Technical Skills

S

trong Python and/or JavaScript/Node.js - clean, production-grade code

S

olid understanding of deployment pipelines, CI/CD, environment management, and secrets handling

E

xperience with vector databases and embedding-based retrieval

C

omfortable with cloud infrastructure (AWS and/or GCP) and cloud-native application patterns

F

amiliarity with monitoring, logging, and alerting for production systems

Soft Skills

H

ighly autonomous - identifies problems and ships solutions without waiting to be asked

E

ffective communicator across technical and non-technical audiences

S

trong product instincts: can step into ownership of an initiative when there's no PM in the room

C

alm under pressure; reliable when other teams are blocked and need answers fast

C

omfortable working across many different teams and problem domains simultaneously

Bonus Points

E

xperience with AI agent frameworks

B

ackground in high-volume performance advertising, media, or creative production

E

xperience with AI in a production context

M

ulti-step agentic pipeline design or large-scale workflow orchestration

E

xperience with data pipelines or BI tooling

Benefits
Health, Vision & Dental coverage  
Unlimited PTO  
401(k) + Matching  
Life Insurance  
Paid Sick Days  
Paid Parental Leav