About the role

Senior Fullstack Engineer developing AI features for Contentsquare's experience analytics platform. Working on exciting product initiatives leveraging Large Language Models for enriching user interactions with digital experiences.

Responsibilities

We're looking for a Senior Fullstack Engineer (Applied AI) to join one of several exciting product initiatives currently in progress that leverage the latest in AI, particularly using Large Language Models (LLMs).
One example project is extending our AI CoPilot product (currently only available in Heap) to more surfaces, allowing users without expertise in product or digital experience analytics to answer their questions simply by asking them.
We are moving rapidly to leverage LLMs to reduce time to insight, make setup easier, and much more.
As our next Senior Software Engineer (Applied AI), you will be focused on product development, with a side of early product iteration.
For example, we expect engineers to participate in user interviews as we validate product hypotheses.
This is an exciting opportunity to work in a “startup within the startup.”
We move quickly from idea to proof of concept to interview to product, ensuring that what we build provides actual value to our customers.
As LLMs and the related technologies are growing and changing rapidly, we are enthusiastic about new ideas and libraries but discerning – what we build is foundational.

Desire to work in a fast-paced development environment where the customer is in the loop. We prefer to fail fast and start over than to learn too late that we’ve built the wrong thing.
Strong motivation to build an AI feature.
Extensive fullstack web application development experience (5+ years), preferably in a data-related industry.
Experience with Typescript, with a variety of front-end frameworks (React, Vue, Node...).
Strong opinions, weakly held about how to evaluate the performance of an LLM-based application.
Experience bringing an application built on top of LLMs from inception to market.
Ability to iterate/prototype rapidly to answer data-related using LLMs (and other ML when appropriate).
Awareness of what LLMs are good at, what they’re not good at, and how to navigate this.
Familiarity with various LLM providers and their relative tradeoffs.

Virtual onboarding, Hackathon, and various opportunities to interact with your team and global colleagues both on and offsite each year
Work flexibility: hybrid and remote work policies
Generous paid time-off policy (every location is different)
Lifestyle allowance
A Culture Crew in every country we’re based in to coordinate regular activities for employees to get to know each other and bond outside of work
Every full-time employee receives stock options, allowing them to share in the company’s success
We have multiple Employee Resource Groups, that offer a safe space for individuals who share common identities, life experiences, or allyship to connect, support one another, and passionately advocate for the issues close to their hearts
And more benefits tailored to each country