Job description

As Hebbia’s first prompt engineer, you will be at the forefront of a new art: teaching, instructing, and programming large language models to get the best from them.

Your role is to deeply understand our users’ needs, figure out and test the best way to prompt models to meet these needs, and then teach our users. You’ll work closely with our customer success, engineering, and product teams.

This role is based out of our New York City office in Soho.

Responsibilities

1. Understand our users’ needs: spend time with our users, deeply understand their explicit and implicit needs and where Hebbia can add the most value
2. Figure out and test the best way to prompt models to meet these needs: discover the best way to prompt models - thinking through typical use cases and edge cases; and test - code your changes into the tool and continue to refine
3. Work with engineering and product teams to implement best practices into tool: help engineering team code changes into tools, work with product teams to iterate on use cases and work flows
4. Teach users: Share best practices with users, customer success & sales teams through documentation, onboardings etc.

Who you are

- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

- Proficiency in Python and popular machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) for model development and deployment

- Experience in AI or LLM product development preferred

- High level familiarity with architecture and operation of large language models

- Customer obsessed: extremely excited about diving deeply into user needs and workflows, and getting the best out of our tool for them

- Problem-solving and analytical skills: Ability to logically break down complex problems, propose precise but innovative solutions, think through edge cases

- Persistence and pace: iterate repeatedly and at pace to improve our prompting for users

- Communication: excellent communicator - with users, engineers, product teams - particularly adept at explaining complex technical concepts to non-technical audiences

- Leadership and teamwork: Proven experience collaborating with cross-functional teams. Strong interpersonal and communication skills to foster a collaborative and inclusive work environment.