Prompt Engineer
Confirmed live in the last 24 hours

11-50 employees

AI copilot for structuring unstructured document workflows
Company Overview
Hebbia AI, a leader in document workflow solutions, offers a unique platform that enables users to efficiently extract, compare, and structure data from unstructured files, setting it apart from competitors. With a robust funding background from industry giants and a dynamic team, Hebbia fosters a culture that values mastery, optimism, and diversity, making it an ideal workplace for those seeking to thrive in a challenging and inclusive environment. The company's commitment to technical excellence is evidenced by its 15-year journey to develop a truly effective AI search technology.
AI & Machine Learning
Financial Services

Company Stage

Series A

Total Funding





New York, New York

Growth & Insights

6 month growth


1 year growth


2 year growth

New York, NY, USA
Experience Level
Desired Skills
Data Science
AI & Machine Learning
  • 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
  • Understand our users' needs: spend time with our users, deeply understand their explicit and implicit needs and where Hebbia can add the most value
  • 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
  • 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
  • Teach users: Share best practices with users, customer success & sales teams through documentation, onboardings etc