Senior AI Workflow & Systems Engineer

Role Description

Build and run the AI infrastructure that powers every team at TubeScience.

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.
• 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.

Qualifications

• 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.

Requirements

• 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

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