Job description
At Emi Labs we are on a mission to increase Frontline Workers’ access to professional opportunities.
This is a 2.7 billion population that accounts for 80% of the world’s workforce. They are digitally invisible, as there’s little to no data available on who they are, their career history, or their skill set, limiting their access to professional opportunities and growth. We're here to transform this by building the infrastructure to make Frontline Workers visible.
Our first step to achieving our mission is to transform the recruiting experience into an easy, human and fair process, for both candidates and companies with high-volume job openings.
Emi, our main product, is an A.I. recruitment assistant that enables companies to engage in a conversation with each applicant to detect interested and qualified individuals while saving Recruiters a huge amount of time by automating tasks such as screening, validating skills, scheduling interviews, and collecting documents.
We were part of Y-Combinator's Winter 2019 batch and in 2022 we have raised an $11M funding round co-led by Merus Capital and Khosla Ventures.
About our Interview Team
An interview is the most crucial moment in a talent acquisition process. The Interview Team is responsible for smart interview scheduling and feedback reception. In a context where frontline candidate assistance to interview is very low (10% - 50%), building tools to make effective scheduling has a great impact on both recruiters and candidates.
What you'll be doing
As a Backend Engineer on the Interview Team, you’ll design and build the orchestration of several modules involved in interview scheduling and execution. In addition to strong backend fundamentals, this role expects a hands-on approach to leveraging AI tools and developing AI-powered agents to automate workflows, reduce manual effort, and increase the team’s overall efficiency and impact.
You’ll work across system architecture, high-level programming, testing, and systems integration, while continuously exploring how AI can be applied to improve internal processes, developer experience, and product capabilities.