- You've personally built and shipped agentic systems with real users in the last 12 months. Not evaluated or piloted: shipped. Be ready to walk us through one (or a side project): the architecture, what failed, what it cost, and how you knew it worked.
- You can tell us how you'd measureAI effectiveness. "Everyone has a license" isn't an answer. We want your opinion on the metric, and on what it would get wrong.
- You'd rather grow output than headcount. You've changed how you and your engineers work because of AI, and raised your expectations of the team to match.
- You've managed engineers and still build. 7+ years of software engineering, including 2+ years managing, on a team small enough that you stayed in the code.
- A scrappy generalist with cross-functional instincts. You've sat inside a sales, marketing or operations team's workflow, understood it, and helped them adopt something new.
- You tie engineering work to business outcomes like pipeline, revenue, time saved or cost avoided, and report on them clearly.
- You're comfortable building the process where there isn't one, and only as much process as the team needs.
Personal Information: Notice at Collection for Employees and Applicants https://drive.google.com/file/d/1FF_5dYGdwHfNCMqV4X9NSnCLdnk9z7Ms/view?usp=sharing
Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired.
Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.