Senior AI Workflow & Systems Engineer
TubeScience · Los Angeles, CA
$110,000–$160,000from the description
Jul 23, 2026
Los Angeles, CA
Jul 25, 2026
What this job asks for AI summary
A hands-on engineering role responsible for building, deploying, and maintaining the AI infrastructure that serves all teams at a performance advertising studio. Day-to-day work spans designing agentic pipelines and LLM-powered applications, managing cloud deployments and serverless infrastructure, and acting as the primary technical resource when other teams hit walls with AI systems. Suits an engineer with a solid software or DevOps foundation who has moved into applied AI.
Senior level · 4+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 6,100 people nationally plausibly meet what this posting asks for (software developers). range 4,600–11,500
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
The role is posted fully remote with Los Angeles preferred; two compensation bands are given — $70,000–$120,000 for remote and $110,000–$160,000 for Los Angeles. The higher (LA) band is reported here as the primary figure; both bands are noted for context.
SOC classification is Medium confidence: the role blends software development (building LLM-powered apps, agentic pipelines, REST integrations) with infrastructure/DevOps ownership (deployment, secrets management, monitoring). The primary day-to-day work leans toward building and shipping AI applications, supporting 15-1252; 15-1244 is the runner-up given the infrastructure and systems administration emphasis.
Python and JavaScript/Node.js are listed as 'strong … and/or' — they are presented as interchangeable primary languages, so they are captured as mutual alternatives under a single hard gate rather than two separate required skills.
Vercel, AWS, and GCP appear together in the requirements section as deployment platform options ('Vercel, AWS, GCP, or equivalent'); Vercel is used as the primary name with AWS/GCP as alternatives. AWS and GCP are also called out separately as a cloud infrastructure requirement, so AWS is retained as a standalone required skill with GCP as its alternative.
n8n, Make, Zapier, and LangChain are listed together as orchestration tool examples ('n8n, Make, Zapier, LangChain, or equivalent'); n8n and LangChain are each emitted with the others as alternatives to reflect that any one satisfies the requirement.
RAG, AI agent frameworks, data pipelines, and BI tooling appear under the 'Bonus Points' section and are marked preferred accordingly.
The '4–6+' years range maps to the overall years minimum of 4 (the stated minimum).
Read the full posting
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