AI Engineer

SafeBase is the leading trust center platform designed for friction-free security reviews. With our enterprise-grade Trust Center Platform, we automate the security review process and transform how you communicate your trust posture, ditching outdated 'security through obscurity' in exchange for transparency that helps you build customer trust, gain valuable insights, and elevate your security story.

SafeBase is looking for an AI Engineer with a background in building and improving AI pipelines and workflows to solve real customer problems to join our team.

How You'll Make an Impact:

• 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.

We’re Looking for Someone Who Has:

• 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. You understand the main focus for engineers at a product-led startup is delivering the right features at the right time.
• 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. Knowing where to cut corners and where to excel.
• 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

Bonus If You Have:

• 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.

Education Requirements:

• Degree in Computer Science, Engineering, or a related field with a focus on machine learning or artificial intelligence.

Salary Range: $175,000-230,000 (Please note, the exact compensation will depend on the level of experience and expertise)

Job descriptions are just a description. SafeBase is full of curious optimizers, which is why we value unique experiences, abilities and opinions.  If this role sounds like your next adventure, but you don’t feel entirely qualified, apply! We value candidates who own it, and if you’re relentlessly resourceful too, you might be exactly who we are looking for. 

Remote @ SafeBase

We believe that working remotely shouldn’t cause any barriers to a great employee experience, so from onboarding to day to day operations, when you work remotely at SafeBase your colleagues and leaders are only as far as a *virtual* tap on the shoulder away. Our roles require 10% travel as we like to meet yearly for collaboration. 

Core Values

Customer-First: We prioritize our customers over the long term and value our reputation above short-term gains.
Extreme Ownership: We take pride in the quality of our work and the success of the company. We take accountability and act like owners, not renters.
Hunger: We find ways to get more done with less, ruthlessly prioritizing to operate with the necessary speed without sacrificing quality.
Win and Fail Together: Our combined success relies on effective communication, collaboration, assuming best intent, and a culture of continuous learning.