Remote AI Engineer

Summary

Join SafeBase as an AI Engineer to apply Retrieval-Augmented Generation (RAG) processing to our trust data platform, design and implement AI pipelines for our AI-based product offerings, and work closely with founders and leadership to shape the future of our AI solutions.

Requirements

• Entrepreneurial mindset - previous experience as an early joiner in a technology startup or evidence that you are scrappy with a 'get-it-done' attitude. You thrive in an ambiguous environment and you enjoy leading people towards a common goal
• Strategic infrastructure and architectural vision. Be able to learn the product & business context to inform tradeoff decisions regarding work scoping, technical debt, and strategic investment
• At least 1 year of experience in building AI-driven products
• Advanced expertise of prompt engineering, RAG pipelines for LLM applications, evaluation & improvement of LLM applications over time, experience taking a data-driven approach to building & iterating on LLM-powered applications
• Degree in Computer Science, Engineering, or a related field with a focus on machine learning or artificial intelligence

Responsibilities

• Apply Retrieval-Augmented Generation (RAG) processing to our trust data platform in order to create an AI agent that is excellent at answering trust-related questions
• Design, implement, and deploy AI pipelines for our AI-based product offerings
• Continuously experiment to improve our pipeline and run quantitative evaluations to make our AI product into something our customers can't live without
• Work closely with the founders and leadership as our first AI Engineer and help shape the future of our AI solutions
• Help grow our platform to thousands of SaaS vendors, like OpenAI, LinkedIn, Dropbox, and Datadog

Preferred Qualifications

• Experience at a B2B SaaS product startup. Even better: product-led startup or a product in cybersecurity/compliance realm
• Experience with NLP / NLU fundamentals (e.g. text tokenization / embedding, text classification, traditional machine learning model development experience, especially for natural language-based models
• Experience with our modern web application tech stack - TypeScript, Node.js, React, Gemini/Vertex (Google Cloud Platform), Vellum, Postgres, Cypress, Jest