Overview

Prentis AI is a new AI research lab, launched in April 2026, focused on building \"computer use\" models - AI trained to navigate the routine digital workflows office workers handle (documents, systems, forms), with the goal of deploying agents that automate tasks like processing insurance claims or handling customs duty refund exceptions without human intervention.

Responsibilities

• End-to-End Product Development: Design, build, and deploy user-facing products powered by LLMs and autonomous agents.
• Data Pipeline Engineering: Architect and maintain robust, scalable ETL/ELT data pipelines to ingest, clean, and process structured and unstructured data (including audio and text) for model fine-tuning and RAG systems.
• Agentic Workflows: Develop and orchestrate complex agent behaviors, including multi-step reasoning, tool integration (APIs, databases, search), and memory systems.
• Concept to Reality: Rapidly prototype new concepts, iterating from initial ideation to production-ready, interactive applications.
• AI Integration: Utilize frameworks like LangChain, LlamaIndex, AutoGen, or custom orchestrators to embed AI capabilities into scalable software architectures.
• User Experience: Bridge the gap between raw AI outputs and intuitive user interfaces, ensuring the product is reliable, responsive, and easy to use.
• Collaboration: Work with ML researchers to leverage custom models and fine-tuned deployments, implementing them effectively into product features.
• Observability: Implement monitoring solutions to track agent behavior, handle edge cases, mitigate hallucinations, and ensure reliable production performance.

Qualifications

• 5+ years of software or product engineering experience, with a proven track record of shipping scalable user-facing applications.
• Data Engineering Expertise: Strong experience building data pipelines, working with streaming data, and managing databases (SQL, NoSQL, Vector DBs like Pinecone or Chroma).
• AI/LLM Experience: Hands-on experience building with LLMs, RAG (Retrieval-Augmented Generation) architectures, and agentic frameworks.
• Technical Stack: Strong proficiency in Python and modern full-stack web technologies (e.g., TypeScript, React, Node.js).
• Prompt & Pipeline Engineering: Deep understanding of prompt engineering, model orchestration, and context window management.
• Infrastructure: Experience with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and deploying web applications.
• Product Mindset: A strong focus on user experience and practical problem-solving.
• Communication: Excellent written and verbal communication skills in English.

Nice to have

• Demonstrated experience shipping at least one AI-native or agent-driven product to active users.
• Contributions to open-source AI, agentic, or software development projects.