9 дней назад
AI Automation Engineer Intern
30$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Automation Engineer Intern (AI automation and workflow systems): Building reliable internal automations with AI tools, workflow platforms, APIs, scripts, and data sources with an accent on user workflow discovery, testing, monitoring, and adoption. Focus on shipping a production automation within 30 days, adding logging, alerts, retries, permissions, and human review, and measuring the impact of three to five adopted automations within 90 days.
Location: Hybrid in Los Angeles, California; in-office Monday, Tuesday, and Wednesday
Compensation: $30 per hour
Company
is a revenue marketing agency that builds pipeline-focused systems for startups and Fortune 500 companies.
What you will do
- Interview users and map current workflows before building automations.
- Prioritize automation opportunities by value, frequency, risk, and effort.
- Build internal automations 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 needed.
- Document workflows, train users, and measure adoption, time savings, error reduction, and cycle-time improvements.
- Ask for support early when data, access, security, or scope is unclear.
Requirements
- Evidence of shipped automations, including links, screenshots, code, or documentation.
- Clear explanation of the exact personal contribution to each project.
- At least one end-to-end example covering the user problem, implementation, testing, and result.
- Familiarity with automation platforms, AI engineering tools, APIs, or scripting.
- Ability to debug, verify, test, document, and monitor AI-assisted work.
- Availability to work hybrid in Los Angeles on Monday, Tuesday, and Wednesday, with a stated start date and weekly availability.
Culture & Benefits
- Work on real internal workflows with supervision and increasing ownership.
- AI-native environment where AI is used to improve speed, quality, judgment, and leverage.
- AI-generated work requires testing, source checks, access controls, and human review.
- Performance is measured through shipped, adopted, documented, and monitored automations.
Hiring process
- Application and evidence review.
- Technical and workflow screen, followed by a paid or clearly bounded skills exercise.
- Live review of the build and debugging choices, references, and final decision.
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