AI Engineer

As a AI Engineer, you will be a core contributor to Zyphra’s Agentic Systems and Interaction projects. You will be at the forefront of building a next-generation desktop and browser-based agent that can autonomously navigate the web, interact with filesystems, and complete complex user tasks. This role spans frontend interfaces, secure sandboxing environments, large-scale document search and retrieval, and language/vision model integration.

• Design and implementation of an agentic system capable of interacting with browsers, operating systems, and enterprise filesystems

• Building search and retrieval pipelines across large-scale structured and unstructured data

• Integrating LLMs, vision models, reinforcement learning, and scaffolding frameworks for autonomous, multi-step decision-making

• Engineering secure virtualized runtimes and backend services for agent execution

• What matters most is your drive to build production-grade ML systems that push the boundary of what software agents can do

• We value velocity and curiosity, especially in fast-moving and ambiguous environments

• Proficiency in Python and a deep understanding of building and debugging complex ML-driven applications

• Experience working with desktop operating systems (Windows and macOS), including APIs for screen reading, file interaction, and accessibility frameworks

• Experience developing browser extensions or automation tools with fine-grained control over the browser (mouse, tabs, DOM)

• Understanding of LLMs, prompting techniques, and orchestration frameworks for multi-step reasoning

• Ability to work across the full ML stack, from model integration to serving infrastructure

• Experience designing or working with secure and virtualized execution environments

• Excellent communication and collaboration skills across product, research, and engineering teams

• Experience building or integrating retrieval-augmented generation (RAG) systems

• Experience working with enterprise security and compliance frameworks (e.g., SOC 2)

• Familiarity with vector databases and large-scale document indexing

• Knowledge of web automation tools and headless browser environments (e.g, Puppeteer, Playwright)

• Understanding of sandboxed or containerized compute environments with strict access controls

• Comfort designing user-facing agentic workflows and reasoning systems that span multiple modalities (text, vision, actions)

• Experience using and fine-tuning models for screen reading, OCR, or UI understanding

• Background in HCI or interest in building intuitive agent interfaces that extend human capabilities