Senior Technical Recruiter
Fractional AIAbout the role
About Fractional AI
Fractional AI builds bespoke gen AI software to transform businesses.
Every C-suite in the country is trying to bridge the gap between AI in theory and AI in practice. We close this gap with exceptional engineering talent and custom end-to-end AI builds (see some of our case studies to learn more).
By joining Fractional AI, you’re stepping onto a San Francisco and NYC-based team working on gen AI projects for top companies from the comfort of an engineering-first startup.
About the role
Our talent is our business. Customers choose us because we offer the elite engineering expertise to build genAI solutions for their unique needs.
As a part of our talent acquisition team, you will be at the forefront of attracting, evaluating, and building our team, shaping our recruitment process for the next 100+ hires.
What you’ll do:
Source talent: From outbound email campaigns to in-person events, you’ll leave no rock unturned to identify the best full-stack engineers to join Fractional AI.
Partner with candidates through the recruitment cycle: From the first phone call through the offer extension, negotiation, and every step in between, you seek to deeply understand candidates, their motivations, and how they can uplevel our team.
Build an exceptional recruiting process: You’ll have the greenspace to design a recruiting process that is inclusive, AI-augmented, data-driven, and committed to an exceptional candidate experience.
Shape our employer brand: You’ll be a key ambassador for Fractional AI, our business, and our team. You’ll shape how we market and attract top engineering talent.
Develop the talent acquisition function: Bonus for experience scaling a recruiting team from the early stages.
What you bring to the table:
Demonstrated excellence: Proven success hiring Staff, Principal, and Senior Engineers at early stage companies.
Empathy. You are quick to understand and relate to others. You seamlessly build trusted relationships – with candidates, hiring managers, interviewers.
Data-driven problem-solving skills. You consistently run experiments, measuring new approaches to reach your goals. You consistently leverage data to drive decision making.
Track record of building inclusive recruiting infrastructure. You design equitable, exceptional hiring processes that identify top talent.
Technical fluency. You understand the nuances of different engineering skill sets and how they match the needs of the team (e.g., what is Kubernetes? What is React?).
Unrelenting reliability. Balls don’t drop on your watch. You balance an attention to detail with an awareness of the big picture to get things done.
Obsession with building leverage. If you have to do the same thing twice, you look for a way to automate. You default to using AI to augment your effectiveness.
Why you should (and shouldn’t) join us
We believe in transparency and know joining a company is a big decision. We’re not the best fit for everyone and try to be clear on what we are and what we’re not so you make the choice that’s right for you.
Why join Fractional?
A front-row seat to the AI revolution: After just one year, Fractional AI has executed many 0-to-1 genAI builds for leading companies. You will be among the handful of teams who have deployed AI solutions across multiple industries at scale.
A huge and growing problem space: Getting genAI into production is the challenge of our time – with legacy consulting firms already driving several billion dollars per year on genAI advising revenue. Most offerings on the market don’t meet the need – they are one size fits all product solutions or advising services without the engineering team to deliver. We offer the engineering talent to meet the need.
A team of veteran founders: The team is built from multi-time founders and co-founded by Travis May, former CEO of LiveRamp and founder + former CEO of Datavant.
Why shouldn't you join Fractional?
We are unapologetically building an engineering-first culture. This is how we build the team to meet the moment. We
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