Staff/ Sr. Staff Software Engineer - Core Platform @ JazzX AI

About SAIGroup SAIGroup is a private investment firm that has committed $1 billion to incubate and scale revolutionary AI-powered enterprise software application companies. Our portfolio, a testament to our success, comprises rapidly growing AI companies that collectively cater to over 2,000+ major global customers, approaching $800 million in annual revenue, and employing a global workforce of over 4,000 individuals. SAIGroup invests in new ventures based on breakthrough AI-based products that have the potential to disrupt existing enterprise software markets. SAIGroup’s latest investment, JazzX AI, is a pioneering technology company on a mission to shape the future of work through an AGI platform purpose-built for the enterprise. JazzX AI is not just building another AI tool—it’s reimagining business processes from the ground up, enabling seamless collaboration between humans and intelligent systems. The result is a dramatic leap in productivity, efficiency, and decision velocity, empowering enterprises to become pacesetters who lead their industries and set new benchmarks for innovation and excellence.Role Overview We are hiring an experienced, hands-on systems and AI Staff/Sr.Staff engineer to help build and operate the core, differentiated AI capabilities in the JazzX platform. You will be a technical leader and hands-on builder, collaborating across multi-disciplinary teams to deliver on our strategic roadmap. This is a pivotal technical role to scale multi-agent systems, adaptive AI learning loops, and real-time orchestration infrastructure that enables enterprise-ready autonomy. Key Responsibilities Platform Architecture & Intelligent Orchestration Build scalable, intelligent backend systems that power real-time orchestration of AI-driven workflows across the enterprise. Design and implement infrastructure that enables collaborative AI agents to communicate, coordinate, and solve complex tasks together. Build flexible memory and context management systems that allow AI components to retain knowledge, personalize behavior, and reason over past interactions. Contribute to adaptive learning pipelines that help the platform continuously improve through feedback, fine-tuning,…

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