• Diseñar e implementar soluciones de IA para procesamiento inteligente de documentos. • Desarrollar pipelines de extracción de información utilizando LLMs, Prompt Engineering y Azure AI. • Integrar y optimizar servicios de IA con herramientas como Claude Code y plataformas cloud. • Definir estándares de calidad, documentar arquitecturas y colaborar en equipos ágiles. • Impulsar la evolución de la solución hacia un entorno de producción robusto, seguro y escalable.

• Working with our customers’ teams, you’ll lead and contribute to all phases of the Neo4j PreSales projects • Be an integral part of the Neo4j sales team, helping to persuade prospective Neo4j users of the benefits and advantages of graph database technology • Position the Neo4j technology within the customer’s environment and architecture • Discuss solution architectures with our customers to address the technical requirements of our customers’ projects • Design and build prototype solutions that demonstrate required functionality with Neo4j • Help prepare solution proposals for our customer’s engineering and management teams that help address the overall project goals

• Find high-leverage opportunities: Run listening tours and current-state assessments across functions. Identify and prioritize the workflows where AI can deliver outsized impact, weighing impact potential against feasibility, and focus on opportunities that can materially bend the revenue/opex curve. • Prototype and validate: Take prioritized use cases from idea to working prototype — internal workflow automations, reusable prompt systems and templates, AI-enabled tools and assistants, and early workflow integrations — to test whether an opportunity is worth broader investment. • Partner across the business: Work directly with functional owners, the AI Enablement Council, and AI Ambassadors to understand real workflow needs, validate selected opportunities, and build the business case and evidence base needed to inform investment decisions. • Build responsibly: Build and test using approved tools and established Legal and Security review pathways. Validate outputs, ensure clear human review, and maintain strong data hygiene. No AI tool is used on Chainguard, customer, or personal data until it has cleared review. • Make it visible and reusable: Document what you built, the problem it solves, and what you learned. Share your work across the company through Builder Hours, demos, and showcases, and surface recurring technical needs and reuse opportunities back to the AI Enablement Council. • Set the standard for internal AI building: Model responsible, high-quality AI building so that what you prototype can be handed off, scaled, and maintained by the functional experts who own the workflow.

• Act as the technical integration expert across enterprise implementations, joining solution and discovery conversations when they turn to ATS, Workday/HRIS, SSO, Outlook/Microsoft 365, data flows, field mapping and integration options • Lead integration discovery - understanding the customer's tech stack, map their requirements to Spotted Zebra's integration capabilities, and translate business goals into a workable technical design • Design and document field mappings, data flows and integration approaches, including the source of truth between systems such as Workday and Spotted Zebra, and what is standard versus bespoke • Scope and confirm technical feasibility - what's available today versus on the roadmap - giving customers honest, credible answers and escalating to the Product Delivery Manager and Product only by exception • Support pre-sales as the integration expert - joining sales conversations with prospects to assess feasibility, answer technical questions, scope requirements, and contribute to RFPs and security questionnaires so deals are set up to succeed at implementation • Act as the customer-facing front of our Product Integration Engineering team - translating customer requirements into clear integration specs, working primarily with that team's Product Manager (and directly with engineers when needed) to get integrations built, and keeping the customer informed throughout • Own the integration workstream alongside the Implementation Manager - spotting risks early, coordinating with Product Integration Engineering, troubleshooting issues, and keeping delivery on track to go-live • Partner with the Skills Science Solutions Consultant on what assessment and AI Interview evidence is appropriate to share back into the ATS, and with the Product Delivery Manager on feasibility and customer-specific product work • Support phased approaches - enabling customers to go live without a full integration and add ATS/Workday integration later • Build repeatable integration playbooks, templates and documentation, and feed integration insights back to Product and Engineering to make delivery more scalable • Provide input to information security, SSO/identity and supplier onboarding conversations as needed • Help shape the integration roadmap - channelling customer needs, recurring requirements and field insights to the Product Integration Engineering team's Product Manager to inform priorities and influence what we build next