About the Role
We’re looking for an AI Engineer to help shape how our platform uses large language models (LLMs) to deliver meaningful, real-world value. You’ll focus on building and improving LLM-powered products — from designing and testing prompts to evaluating and optimizing model performance.
This is a highly collaborative, product-focused position where you’ll partner with product managers and engineers to turn cutting-edge AI capabilities into practical, scalable features. The role is fully remote within the U.S., ideal for someone who thrives in a fast-moving, distributed environment and communicates clearly and proactively.
Responsibilities
- Prompt Engineering: Design, test, and refine prompts and system instructions to enhance LLM performance and reliability.
- LLM-Powered Features: Build and integrate backend features leveraging LLMs to improve analytics and intelligent user experiences.
- Model Evaluation: Create evaluation frameworks to assess and monitor LLM output quality across multiple use cases.
- Continuous Improvement: Iterate based on metrics, internal testing, and user feedback to improve prompt and model accuracy.
- Coding & Integration: Write and maintain production code (primarily in TypeScript and some Python) to support LLM interactions, including RAG pipelines, embeddings, and content chunking of large documents.
Qualifications
- 3+ years of experience in software engineering and AI/LLM development (open to less for exceptional candidates).
- Hands-on experience with TypeScript, Python, and cloud services.
- Strong understanding of NLP, vector databases, and RAG architectures.
- Proven ability to evaluate and improve model outputs systematically.
- Self-directed, highly collaborative, and comfortable working in a remote, asynchronous setup.
Tech Stack
TypeScript, Python, Large Language Models (LLMs), Prompt Engineering, Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Vector Databases, APIs, Cloud Services
Job Type: Full-time
Pay: $190,000.00 - $250,000.00 per year
Work Location: Remote
