4+ years as a software engineer, data engineer, or AI/ML practitioner writing technical design documents, data pipeline documentation, or API specifications
Manage the collection, cleaning, synthesis, and annotation workflows for post-training data; participate in annotation guideline development and vendor coordination.
Zero bureaucracy, direct executive alignment. Bypass middle management and work face-to-face with the founders, CTO, and AI leaders to architect solutions and steer the company’s technological future.
Architect and scale enterprise-grade GenAI and Agentic AI solutions, including orchestration, RAG, tool use, memory, evaluation, safety and human oversight.
Collaborate with back-end developers on API integration and end-to-end system functionality, with hands-on involvement in Node.js (JavaScript / TypeScript) back-end development where required.
Develop agentic AI solutions for engineering use cases, including workflow and multi-agent orchestration, as well as integration with engineering tools and data sources such as CAD/CAE, simulation, PLM and internal knowledge systems.
Own the multi-factor authentication orchestration layer — verification strategy, step-up logic, and user-level customization — balancing security strength against completion rate with measurable outcomes