At Exa, we're building a next-generation AI search engine—one that outperforms Google for power users. We help people find the information they can’t get anywhere else: https://exa.ai/websets
We're an SF team of ~35 from Harvard, MIT, Google, Apple etc. We recently raised a Series B from Benchmark, and we are rapidly building the most intelligent search engine in history.
Now, we’re looking for a Remote Executive Assistant to help our C-suite and wider team run smoothly!
About the Role
As an Executive Assistant at Exa, you will support both our C-suite and broader team with scheduling, coordination, and day-to-day operations. This will be a highly variable role where new and unexpected tasks come up often, and you’ll play a key role in keeping the company organized and unblocked.
What You’ll Do
Own calendar management and scheduling for C-suite and key team members
Continuously find ways to improve workflows, scheduling systems, and recurring processes
Support recruiting coordination, including interview scheduling and candidate logistics
Comfortable working with modern tools — bonus if you enjoy automating parts of your own role
Support team coordination, virtual events, and occasional offsites
Ad hoc tasks as they come — be ready for anything!
What You’ll Need
2+ years of experience as an executive assistant or in a similar role
Excellent communication and organizational skills
Ability to self-organize and work independently with little direction
Enjoy context switching between different priorities and workstreams
Strong people instincts — you know when to step in, how to help, and when to stay out of the way
Comfortable in a fast-moving, high-growth startup environment
Experience working remotely and communicating across time zones is a plus
This is a fully remote role. Candidates should be comfortable collaborating with a US-based team and overlapping with Pacific Time work hours.
Top Skills
What We Do
Exa was built with a simple goal — to organize all knowledge. After several years of heads-down research, we developed novel representation learning techniques and crawling infrastructure so that LLMs can intelligently find relevant information.
