• AI Products & Solution Architecture: • Design and guide implementation of AI-driven products, APIs, and platform features from concept to production; • Evaluate, select, and benchmark AI/ML models — including frontier LLMs, fine-tuned models, and open-source alternatives; • Architect scalable, observable, and cost-efficient AI systems that span experimentation, staging, and production; • Collaborate with product managers and business stakeholders to translate requirements into robust solution architectures; • Establish architectural standards for multi-agent systems, including context management strategies and memory designs. • Agentic AI & Process Automation: • Identify business processes that can be automated or enhanced via agentic AI, and define the architecture for doing so; • Design and oversee implementation of MCP server ecosystems that connect agents to enterprise data sources and tools; • Architect multi-agent workflows using orchestration frameworks (LangGraph, CrewAI, AutoGen), with appropriate human-in-the-loop checkpoints; • Integrate agent-to-agent communication standards (A2A, ACP) where multi-agent coordination is required; • Drive governance of MCP deployments: audit trails, authentication, rate limiting, and access control policies; • Embed AI into internal and external tools to improve operational efficiency across teams. • AI-Augmented Software Engineering: • Set up and continuously optimize AI-augmented developer environments (Claude Code, Cursor, GitHub Copilot); • Introduce AI into automated testing, deployment pipelines, code review, estimation, and technical documentation; • Define and enforce best practices for using AI coding tools safely, securely, and productively in software delivery; • Drive adoption of context engineering disciplines — designing prompts, tool schemas, and MCP resources that maximize agent reliability; • Governance, Security & Responsible AI: • Ensure all AI systems are designed with security-first principles: input validation, output guardrails, and least-privilege access; • Maintain AI compliance standards aligned with GDPR, the EU AI Act, EU Data Act, CRA, ISO27001, and internal model governance policies; • Implement observability and evaluation pipelines to detect hallucinations, drift, and performance degradation in production LLM systems.

• Conduct general and targeted product review and perform specified research consultation (both in-person and virtual) for a curated subscriber list of ~200+ accounts • Provide comprehensive customer service to existing users, including by not limited to: light technical troubleshooting, product access resolution, event and incident tracking and client-facing data reporting • Identify potential new users, new practice area opportunities and other elements of enhanced product adoption • Partner with sister products on the LexisNexis side, including collaboration for multi-product initiatives • Work closely with development teams to provide customer-centric levels of feedback regarding the design and implementation of product enhancements • Partner with the Sales Organization on retention strategies and best practices for the overall Customer Experience • Technical tracking of all activity via CRM tools • Adoption of workflow management tools including but not limited to: CoPilot, PowerAutomate, Salesforce, ChatGPT 5, Gong, and proprietary workflow solutions. • Cultivate and maintain exemplary working relationships with user base and ultimately support the Intelligize NPS and retention goals.

• Building and maintaining relationships with sales reps, partners, customers and other internal stakeholders • Gaining knowledge of HubSpot products for better-proposed solutions • Understanding customer challenges and how to deliver technical value to meet their business goals and objectives • Participating and directing projects relevant to presales, sales, and the wider business • Coaching and mentoring less experienced team members

• Engage with Solutions Architects to understand use case demand plans for prioritized customers • Lead post-technical win account strategy and execution plan • Act as accountable technical leader for specific use cases and customers • Address technical issues related to production/go-live status • Leverage internal resources and escalate to experts as needed • Create and execute strategies for accelerating key use cases into production • Collaborate with Databricks Product and Engineering teams • Develop execution plans covering customer-facing technical roles and activities • Provide KPI reporting on usage and customer health