Applied AI Engineer – Research & IP Indexing

About PIP Labs & Story

PIP Labs is an R&D company contributing to the development of Story, a purpose-built Layer 1 blockchain that transforms intellectual property into a programmable asset class.

Story is designed specifically for intellectual property. With Story, creators and developers can register IP on-chain and define usage rights in seconds, dramatically lowering the barriers created by today’s complex and antiquated IP legal systems.

By making IP programmable, Story creates a transparent, decentralized global repository where AI agents, developers, and businesses can discover, license, and monetize intellectual property through simple API-driven interactions.

Story launched mainnet in February 2025, and the native $IP token is now listed on major global exchanges. We are now entering the next phase of development focused on AI-native infrastructure and agent-driven applications built on top of programmable IP.

PIP Labs is building the core infrastructure that powers this ecosystem, defining how intellectual property is registered, structured, and transacted in an AI-driven world.

As an Applied AI Engineer, you will build the data and reasoning systems that allow AI agents to understand and interact with intellectual property on Story.

You will design and implement indexing, retrieval, and reasoning infrastructure that connects onchain IP data with research datasets and external knowledge sources. Your work will enable AI agents and applications to discover, interpret, and reason over IP at scale.

This role sits at the intersection of machine learning, data infrastructure, and decentralized systems, and is ideal for engineers who enjoy building production systems that power intelligent applications.

• Design and build scalable data ingestion and indexing pipelines for onchain IP and external research datasets

• Develop embedding pipelines and retrieval systems that enable efficient semantic search and reasoning

• Build structured knowledge representations that capture relationships between IP assets, creators, and derivatives

• Deploy and operate production ML systems that support AI-native applications

• Work closely with protocol and application teams to integrate AI capabilities into Story-powered products

• Improve data quality, retrieval performance, and system reliability over time

• 3+ years of experience building production machine learning or data systems

• Strong Python and data engineering fundamentals

• Experience building data pipelines and processing large datasets

• Experience working with embeddings, retrieval systems, or vector databases

• Experience deploying and maintaining ML systems in production environments

• Strong engineering fundamentals and attention to detail

• Interest in AI-native infrastructure and intelligent systems

• IP and research data is structured into reliable, searchable knowledge systems

• AI agents and applications can reason effectively over indexed IP and research data

• Retrieval and reasoning systems are fast, accurate, and reliable

• Product teams depend on your systems to power AI-native workflows