• Determine client needs, recommend the best options to solve challenges • Execute multi-vendor hardware & software to both existing and net new clients • Display expertise in storage, networking, data protection, digital archiving, and other infrastructure technologies • Develop, validate and/or verify rack elevations and cable layouts and lengths • Install server, storage, network and related equipment (“rack & stack”) onsite in remote client locations • Cable and label all types of network cabling within the datacenter environment • Perform general server and network administration to configure basic OS and ILO access • Document all aspects of installation processes from start to finish

• Design, develop, and deploy AI-enabled applications on Microsoft Azure • Build scalable and secure solutions leveraging Azure OpenAI, Azure AI Search, and Azure Cognitive Services • Collaborate with business and technical stakeholders to gather requirements and define solution architecture • Develop robust, production-ready code and integrate Azure AI capabilities into modern applications • Perform testing, optimization, and performance tuning across solutions • Ensure solutions align with cloud security and architectural best practices • Produce technical documentation and implementation artefacts • Translate complex business requirements into practical technical solutions • Work closely with delivery teams to bring AI projects from concept through to deployment • Contribute to continuous improvement and innovation across AI and cloud initiatives

• Establish the core architecture, engineering culture, and security posture, including SOC 2 readiness, tenant isolation, encryption, and audit logging • Ship a marketing review prototype into production with a design partner early adopter, then deliver communications surveillance, trading oversight, audit-ready logs and reporting; release GA v1 covering all core modules except regulatory filings within 9 months, and expand into regulatory filings and enterprise integrations through 18 months • Own the training and constant evolution of the core AI/LLM model, delivering robust and highly reliable analysis • Own the explainability layer that produces audit-ready evidence on demand, and the reliability engineering that ensures the platform performs consistently in the field • Represent the company in front of all customer constituencies and third-party interests, as well as investors, as the technical voice of the venture • Convert pilots into ten paying customers and reach $1M ARR within 18 months, partnering with the CEO on conversion and fundraising • Recruit and lead the founding engineering and applied AI team, and establish the cultural foundation of the company

• Establish the core architecture, engineering culture, and security posture, including SOC 2 readiness, tenant isolation, encryption, and audit logging • Ship a marketing review prototype into production with a design partner early adopter, then deliver communications surveillance, trading oversight, audit-ready logs and reporting; release GA v1 covering all core modules except regulatory filings within 9 months, and expand into regulatory filings and enterprise integrations through 18 months • Own the training and constant evolution of the core AI/LLM model, delivering robust and highly reliable analysis • Own the explainability layer that produces audit-ready evidence on demand, and the reliability engineering that ensures the platform performs consistently in the field • Represent the company in front of all customer constituencies and third-party interests, as well as investors, as the technical voice of the venture • Convert pilots into ten paying customers and reach $1M ARR within 18 months, partnering with the CEO on conversion and fundraising • Recruit and lead the founding engineering and applied AI team, and establish the cultural foundation of the company