# Senior Applied AI Engineer – Enterprise Systems

- **Company:** [TubeScience](/companies/tubescience)
- **Location:** Los Angeles, California, United States
- **Type:** 
- **Posted:** Aug 19, 2026
- **Views:** 1


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## Job Description

&lt;p&gt;&lt;strong&gt;Role:&lt;/strong&gt; Senior Applied AI Engineer – Enterprise Systems&lt;br&gt;&lt;strong&gt;Location:&lt;/strong&gt; Remote (US) or Los Angeles (preferred)&lt;br&gt;&lt;strong&gt;Compensation:&lt;/strong&gt;&lt;strong&gt;&lt;br&gt;&lt;/strong&gt; • Remote: &lt;strong&gt;$70,000–$120,000&lt;/strong&gt;&lt;strong&gt;&lt;br&gt;&lt;/strong&gt; • Los Angeles: &lt;strong&gt;$110,000–$160,000&lt;/strong&gt;&lt;strong&gt;&lt;br&gt;&lt;/strong&gt; &lt;strong&gt;Reports to:&lt;/strong&gt; VP of Information Systems (Eilrama)&lt;br&gt;&lt;strong&gt;Team:&lt;/strong&gt; Information Systems&lt;/p&gt; &lt;h2&gt;&lt;strong&gt;About TubeScience&lt;/strong&gt;&lt;/h2&gt; &lt;p&gt;At TubeScience, we build software systems that combine AI, engineering, and automation to solve complex operational problems at scale.&lt;/p&gt; &lt;p&gt;We’re looking for an engineer who has evolved from systems engineering into applied AI—someone who enjoys designing reliable production systems, integrating modern AI capabilities, and owning them in production.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;This is an internal Forward Deployed Engineering role.&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;Rather than building products for external customers, you’ll work directly with internal stakeholders to identify operational bottlenecks, architect AI-powered solutions, deploy them rapidly, and continuously improve them based on real business needs.&lt;/p&gt; &lt;p&gt;This is &lt;strong&gt;not&lt;/strong&gt; an AI research or model-training position. We apply state-of-the-art AI models to solve enterprise problems through software engineering.&lt;/p&gt; &lt;h2&gt; &lt;/h2&gt; &lt;h2&gt;&lt;strong&gt;The Role&lt;/strong&gt;&lt;/h2&gt; &lt;p&gt;You’ll own the design, implementation, deployment, and operation of AI-powered enterprise systems that automate business processes across the company.&lt;/p&gt; &lt;p&gt;Success in this role means building systems that don’t just work—they continue working reliably after deployment.&lt;/p&gt; &lt;p&gt;You’ll be responsible for the complete lifecycle of production AI systems, including architecture, deployment, monitoring, debugging, incident response, and continuous improvement.&lt;/p&gt; &lt;h2&gt;&lt;strong&gt;What You’ll Do&lt;/strong&gt;&lt;/h2&gt; &lt;ul&gt; &lt;li&gt;Design and build production AI applications that automate complex enterprise workflows.&lt;/li&gt; &lt;li&gt;Architect agent-based systems that coordinate LLMs, APIs, internal services, databases, and business logic.&lt;/li&gt; &lt;li&gt;Build reliable orchestration layers that integrate multiple tools and enterprise platforms.&lt;/li&gt; &lt;li&gt;Deploy production-ready AI systems with observability, monitoring, rollback strategies, and operational safeguards.&lt;/li&gt; &lt;li&gt;Investigate production issues, analyze logs, debug failures, and restore system reliability when incidents occur.&lt;/li&gt; &lt;li&gt;Design scalable architectures that prioritize maintainability, resiliency, and operational excellence.&lt;/li&gt; &lt;li&gt;Partner closely with Product, Operations, Creative, Engineering, and Business teams to identify high-impact automation opportunities.&lt;/li&gt; &lt;li&gt;Rapidly prototype, validate, deploy, and iterate solutions based on production performance and business outcomes.&lt;/li&gt; &lt;li&gt;Continuously improve existing AI systems for reliability, speed, and business impact.&lt;/li&gt; &lt;/ul&gt; &lt;h2&gt;&lt;strong&gt;Who You Are&lt;/strong&gt;&lt;/h2&gt; &lt;p&gt;We’re looking for systems engineers who naturally evolved into building AI-powered software—not AI hobbyists who recently discovered infrastructure.&lt;/p&gt; &lt;p&gt;You likely have:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;&lt;strong&gt;3–6+ years&lt;/strong&gt; of professional software or systems engineering experience.&lt;/li&gt; &lt;li&gt;Experience building and operating production software used by real users or internal business teams.&lt;/li&gt; &lt;li&gt;Strong Python engineering experience.&lt;/li&gt; &lt;li&gt;Experience integrating modern LLMs into production systems using frameworks such as OpenAI, Anthropic, LangGraph, MCP, or similar.&lt;/li&gt; &lt;li&gt;Experience designing systems that coordinate multiple APIs, databases, services, and enterprise applications.&lt;/li&gt; &lt;li&gt;Strong understanding of distributed systems, debugging, logging, monitoring, and production operations.&lt;/li&gt; &lt;li&gt;Experience deploying, operating, troubleshooting, and improving production systems after launch.&lt;/li&gt; &lt;li&gt;Strong architectural thinking with the ability to design complete end-to-end solutions.&lt;/li&gt; &lt;li&gt;Comfort working independently in a fast-paced startup environment.&lt;/li&gt; &lt;/ul&gt; &lt;h2&gt;&lt;strong&gt;Ideal Background&lt;/strong&gt;&lt;/h2&gt; &lt;p&gt;The strongest candidates typically come from backgrounds such as:&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Systems Engineering&lt;/li&gt; &lt;li&gt;Platform Engineering&lt;/li&gt; &lt;li&gt;Backend Software Engineering&lt;/li&gt; &lt;li&gt;DevOps / Infrastructure Engineering &lt;strong&gt;with significant software development experience&lt;/strong&gt;&lt;/li&gt; &lt;li&gt;Internal Developer Platforms&lt;/li&gt; &lt;li&gt;Enterprise Systems Engineering&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;They later expanded into Applied AI rather than beginning their careers in AI.&lt;/p&gt; &lt;p&gt;Experience at a large technology company building production systems is highly valued.&lt;/p&gt; &lt;h3&gt;&lt;strong&gt;Bonus...

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