
AI Squared
Enterprises and federal agencies are investing heavily in AI, but deployment repeatedly fails at the “last mile” leading to the loss of trillions of dollars in wasted investment and lost opportunity. AISquared solves the last mile problem by creating a secure, production-grade way to operationalize AI inside the business applications where work actually happens, without requiring large new engineering lifts, while giving leaders measurable visibility into adoption, performance, and business impact. AISquared provides a comprehensive, low-code platform, UNIFI and Sparx, designed to “CLOSE” the gap between AI potential and real operational outcomes through five core capabilities: 1. Connects by integrating virtually any data source and any AI model using pre-built connectors. 2. Learns by capturing real-time user feedback directly inside the workflow to support continuous model improvement. 3. Orchestrates by managing complex data workflows and policies through a single UI. 4. Secures deployments with defense-grade controls. 5. Embeds insights where work happens by delivering no-code widgets and visualizations or AI chatbots integrated directly into systems. This results in 5x faster time-to-value and measurable ROI that is Trusted by leading financial institutions, complex supply chain organizations, and the United States Department of Defense, AISquared helps organizations move from stalled pilots to real adoption, faster decision making, and measurable operational impact. Learn more at https://aisquared.ai/ Request a demo at https://aisquared.ai/request-demo/
Open Positions at AI Squared
3 open positions
Own quality for an AI product by building automated integration, frontend, and API testing frameworks and driving testing excellence. This remote QA SDET role combines hands-on automation, strategic risk identification, detailed documentation, and cross-functional quality leadership.
Join a distributed engineering team to build secure, scalable backend services and improve system performance and reliability. You’ll own backend architecture while collaborating closely with product and engineering partners.
Build and operate scalable, production-grade ML and LLM systems for a core AI team. This hybrid role focuses on MLOps, deployment automation, monitoring, reliability, and cloud-based performance optimization.