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AI Automation Engineer Intern

📅 Feb 23
AI AutomationWorkflow MappingAutomation PlatformsAI Engineering Tools
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📜 Description

  • Interview users and map workflows before building.
  • Prioritize automation opportunities by value, frequency, risk, and effort.
  • Build internal automations using approved AI tools, workflow platforms, APIs, scripts, and data sources.
  • Test normal cases, failures, permissions, and handoffs; add logging, alerts, retries, and human review as needed.
  • Document workflows, train users, and measure adoption and impact.
  • Deliver one useful production automation within 30 days and three to five adopted automations within 90 days.

🛠️ Requirements

  • Demonstrate technical ability to build and debug automations.
  • Show curiosity about user problems and discipline in testing and documenting work.
  • Provide evidence of automations shipped and describe your individual contribution.
  • Explain an end-to-end example, including the user problem, testing, and results.
  • Show familiarity with automation platforms, AI engineering tools, APIs, or scripting.
  • Describe how you debug, verify, and monitor AI-assisted work.
Full job description

Ship useful automations and learn how production systems really work

We are hiring an AI Automation Engineer Intern to find repetitive work and build reliable systems that give the team more leverage. Include “Automation engineering is cool” in the subject line. Otherwise, your application will be disqualified.

You will work on real internal workflows with clear supervision and ownership. You need enough technical skill to build and debug, enough curiosity to understand the user’s problem, and enough discipline to test and document what you ship.

About Single Grain

Single Grain is a revenue marketing agency. We build pipeline-focused systems that compound, not campaigns that expire. We have helped more than 500 companies, from venture-backed startups to the Fortune 500, drive measurable growth.

We operate as an AI-native team. Every role uses AI to improve speed, quality, judgment, and leverage. AI-generated work still requires testing, source checks, access controls, and human review.

Your mission

Ship adopted internal automations that save time, reduce errors, shorten cycle time, or improve team output.

Primary KPI: deliver the first useful production automation within 30 days and three to five adopted automations within 90 days, with documented baselines and results.

What you will own

  • Interview users and map the current workflow before building.

  • Rank small automation opportunities by value, frequency, risk, and effort.

  • Build with approved AI tools, workflow platforms, APIs, scripts, and data sources.

  • Test normal cases, failures, permissions, and handoffs.

  • Add logging, alerts, retries, and human review where the risk requires it.

  • Document the workflow, train the users, and measure adoption and impact.

  • Ask for help early when data, access, security, or scope is unclear.

What success looks like

In 30 days, you understand the operating environment and have shipped one useful automation with an owner and baseline.

By 60 days, you can independently move a small workflow from diagnosis through production and readback.

By 90 days, three to five automations are adopted, documented, monitored, and producing measured leverage.

Evidence we need to see

  • Links, screenshots, code, or documentation for automations you have shipped.

  • Your exact role and the part you completed without someone else doing it for you.

  • One end-to-end example from user problem through testing and result.

  • Familiarity with automation platforms, AI engineering tools, APIs, or scripting.

  • A clear account of how you debug, verify, and monitor AI-assisted work.

This role is not

  • A course-only internship with no shipped work.

  • A prompt-only role.

  • A role for copying AI output without understanding or testing it.

  • A role that declares success before users adopt the system.

How the process works

  1. Application and evidence review.

  2. A focused technical and workflow screen.

  3. A paid or clearly bounded skills exercise.

  4. A live review of your build and debugging choices.

  5. References and final decision.

Work model and compensation

This is a hybrid internship in Los Angeles. The expected in-office days are Monday, Tuesday, and Wednesday. Pay is $30 per hour. State your start date and weekly availability.

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