Senior AI Systems Engineer — Production & Automation

Tubescience52; Los Angeles (CA); On-site; USD 110,000 - 160,000; Full time

Job summary

TubeScience is seeking a Senior AI Workflow & Systems Engineer to design and operate production AI systems. You will own end-to-end architecture, deployment, monitoring and continuous improvement of AI-powered solutions across internal workflows.

You will work with internal stakeholders to identify bottlenecks, architect reliable AI capabilities, deploy rapidly, and iterate based on real business needs, reporting to the VP of Information Systems.

Qualifications

• 3+ years of professional software or systems engineering experience with production software.
• Applied AI background from systems engineering or infrastructure work, not starting in AI.
• Strong Python engineering experience and production-grade coding practices.
• Experience integrating LLMs into production systems using APIs or frameworks.
• Designing systems that coordinate multiple APIs, databases and services.
• Understanding distributed systems, debugging, logging and monitoring.

Responsibilities

• Design and build production AI applications that automate complex enterprise workflows.
• Architect agent-based systems coordinating LLMs, APIs, internal services and databases with reliable orchestration across platforms.
• Deploy AI systems with observability, monitoring, rollback strategies and operational safeguards.
• Investigate production issues, analyze logs, debug failures and restore reliability.
• Partner with Product, Operations, Creative, Engineering and Business teams to find high-impact automation opportunities.
• Prototype, validate, deploy and iterate quickly based on production performance and business outcomes.

Skills

Python

LLMs in production

Distributed systems

API orchestration

Automation

Independent work

Tools

Docker

Kubernetes

AWS

GCP

Azure

LangGraph

MCP

Temporal

Job description

TubeScience is seeking a Senior AI Workflow & Systems Engineer to design and operate production AI systems. You will own end-to-end architecture, deployment, monitoring and continuous improvement of AI-powered solutions across internal workflows.

You will work with internal stakeholders to identify bottlenecks, architect reliable AI capabilities, deploy rapidly, and iterate based on real business needs, reporting to the VP of Information Systems.