Af
1 - 10 employees
💰 Series A on 2021-04
Intellectual property rights constitute key assets for many of the most successful companies today. The need to identify, protect, and exploit such assets effectively is of great importance. Our qualifications cover all types of intellectual property assets, such as copyrights, trade marks, trade names, patents, design rights, and trade secrets.
AI Engineer
Job not on LinkedIn
🕒 April 1
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Af
1 - 10 employees
💰 Series A on 2021-04
Intellectual property rights constitute key assets for many of the most successful companies today. The need to identify, protect, and exploit such assets effectively is of great importance. Our qualifications cover all types of intellectual property assets, such as copyrights, trade marks, trade names, patents, design rights, and trade secrets.
📋 Description
• Design and develop an AI-powered productivity analytics platform — from data pipeline architecture to the final analytical product that helps teams make data-driven decisions • Build scalable LLM pipelines (Claude, GPT): develop data chunking strategies, implement MapReduce approaches for parallel processing of large datasets, and synthesize results into structured reports and insights • Create a meta-workflow system where LLMs generate, test, and deploy automation scripts in an isolated environment — with automatic self-correction loops and production deployment without manual intervention • Develop system-level prompt engineering: build and maintain a library of prompt templates for various analytical scenarios — from summaries and profiles to deep performance analysis • Build an evaluation framework for AI output quality control: hallucination detection, consistency scoring, regression tests — ensuring the product delivers reliable and reproducible results • Scale the platform to new domains and analysis types without linear growth in manual effort — through an architecture that allows adding new modules via configuration, not code • Document AI architecture, define automation specs, and present product insights to stakeholders and clients
🎯 Requirements
• 2+ years of experience working with LLMs in production: prompt engineering, pipeline development, API integration — with at least 1 year of hands-on experience with advanced features (tool use, structured outputs, agents) • Strong Python skills (async, dataclasses, type hints, API integrations) and a commitment to writing clean, testable, and maintainable code • Understanding of MapReduce patterns for LLM processing: ability to choose chunking strategies, organize parallel processing, and aggregate results into a cohesive analytical product • Experience building agentic systems: tool use, self-correcting loops, multi-agent workflows — and the judgment to know when an agent works better than a rigid pipeline • Proficiency in SQL and experience working with analytical databases • English at C1 level — comfortable reading documentation, writing technical specs, and communicating asynchronously • Ownership mentality: you take tasks end-to-end, debug production issues independently, and iterate to deliver results without micromanagement
🏖️ Benefits
• Competitive compensation and a comprehensive benefits package • The freedom to bring your own ideas to life • Transparent performance evaluation based on individual KPIs • Access to partner programs from Snapchat, Meta, Google, and Apple, along with their best practices • Established processes and no barriers to internal growth • Health insurance and wellness programs
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