Role Description The Solution Engineer is the technical bridge between Gilytics’ engineering and GIS data teams and its customer-facing functions (Sales, Business Development, Customer Success). This role turns Pathfinder’s technical capabilities into compelling, working demonstrations and trusted technical guidance for prospects and clients, covering everything from pre-sales proof-of-concepts to live technical support and customer onboarding. Qualifications - 3+ years of practical experience applying GIS to land, environmental, or infrastructure management - 2+ years in a customer-facing role - Demonstrable experience writing technical documentation in English; conversational English proficiency - Desirable: Experience in teaching or technical training activities - 2+ years working with international customers in an English-speaking context - German, Spanish, or other languages are a plus - Education in Geographic Information Systems, Geomatics, Geospatial Science, Environmental Engineering, or a similar technical/scientific field Requirements - Become a deep expert in the Pathfinder solution and its application across customer use cases - Communicate Pathfinder’s capabilities clearly and persuasively in the context of user needs - Prepare and run demo projects that showcase Pathfinder’s workflows and applications - Prepare technical documentation and contribute content for sales and marketing materials - Prepare technical offers and responses for public tenders - Provide technical support, including live support to customers - Manage and triage customer technical requests to help prioritise the product roadmap - Design and deliver customer onboarding and training activities - Perform holistic testing of the solution ahead of releases and client deployments - Use AI tools to accelerate the build of demo projects, PoCs, and tender responses - Leverage AI writing assistants to draft and translate technical documentation and proposals - Use AI-assisted support/triage tools to manage, categorise, and prioritise incoming customer technical requests - Incorporate AI-assisted testing tools into holistic solution QA to catch issues before they reach clients Benefits - A real, high-impact role from day one — you’ll work directly with leadership (CEO, CTO, GIS Data Lead) on a platform already trusted by major utilities and infrastructure clients - An AI-native workplace, Microsoft Copilot, GitHub Copilot, and other AI tools are built into how we work from day one, not bolted on later - Remote-first, flexible-hours culture, core hours are 10:00–15:00 CET, with full flexibility outside that window; we trust people to manage their time as professionals - A small, multicultural team spanning Spain, Switzerland, LATAM, and Canada, where your work is visible and your voice matters - Structured onboarding with a clear 90-day plan, no sink-or-swim, no guessing what success looks like - Learning & development support tied to your own competence plan, including certifications and AI tooling upskilling - Company equipment provided (laptop and the tools you need to do your job well) - Vacation entitlement and leave terms in line with applicable local labour law - Compensation: competitive and benchmarked to role, experience, and location

• Install and configure laboratory software systems • Integrate software into laboratory workflows, including mapping daily processes • Deliver and implement Laboratory Information System (LIS) projects • Act as a subject matter expert within your field • Serve as a trusted technical contact for customers during projects and assignments • Support the adoption of emerging technologies, including data-driven and AI-enabled solutions • Identify opportunities to optimise laboratory workflows and system performance • Work with the Project Manager or Customer Services Manager and follow their guidance and planning. • Make proposals and identify technical risks, including those related to data integrity and AI-enabled functionalities, and communicate them clearly. • Prepare execution plans and relevant documentation. • Ensure all work is properly documented in internal systems (projects and aftersales). • Deliver assigned tasks according to project plan, budget, and quality standards. • Take full responsibility for all technical aspects of assigned tasks. • Keep stakeholders informed about progress and risks. • Demonstrate flexibility and support on-site customer implementations. • Manage and implement small projects or sub-projects. • Deliver customer training, including guidance on system data usage and reporting capabilities. • Act as interface between customer and development teams. • Organize and execute internal and external project handovers. • Perform update and upgrade projects

• Diseñar e implementar soluciones de observabilidad (logs, métricas y trazas) adaptadas a cada cliente, especialmente con ELK Stack. • Crear dashboards, alertas y visualizaciones avanzadas con Grafana. • Implementar instrumentación en apps y trazabilidad distribuida con OpenTelemetry. • Añadir capacidades de IA a las plataformas de Observabilidad. • Analizar problemas de rendimiento, disponibilidad y capacidad. • Colaborar con equipos de desarrollo DevOps y SRE para mejorar la detección temprana de incidencias. • Documentar buenas prácticas y formar a usuarios técnicos en el uso de las herramientas.

Role Description We are seeking an experienced Lead Rulebook Configurator to lead the configuration and implementation of insurance products, pricing models, underwriting rules, and workflow components within Verisk Rulebook / Sequel Rulebook. The role sits at the intersection of insurance domain, pricing model interpretation, rules configuration, business analysis, and stakeholder engagement. The individual will work closely with senior stakeholders from Underwriting, Actuarial, Operations, Product, IT, and Change teams, primarily in the London Market / specialty insurance environment. The ideal candidate will have a strong configuration mindset, excellent analytical ability, hands-on experience with Rulebook or similar rules/rating platforms, and the confidence to translate complex Excel-based pricing models and underwriting guidelines into structured, governed Rulebook configurations. Key Responsibilities - Lead the configuration of insurance products, rating algorithms, underwriting rules, referral rules, eligibility rules, authority checks, and workflow logic within Rulebook. - Convert Excel-based pricing models into Rulebook-compatible configuration components, ensuring calculation accuracy and business alignment. - Configure rating tables, factors, modifiers, risk attributes, premium calculations, validations, and business rules. - Configure and maintain Rulebook pages, page flows, page linking, product structures, and user journeys. - Support document generation logic, quote outputs, pricing worksheets, and downstream data outputs where applicable. - Ensure reusable configuration patterns are applied across products/classes to improve maintainability and consistency. Business and Domain Analysis - Work with underwriters, actuaries, operations SMEs, and product owners to understand pricing intent, risk appetite, referral logic, and underwriting guidelines. - Challenge and clarify ambiguous business rules before configuration. - Translate business requirements into clear configuration specifications and implementation-ready artefacts. - Identify gaps, inconsistencies, or risks in pricing spreadsheets, underwriting guides, or product documentation. - Support impact analysis for pricing changes, product enhancements, and model version updates. Stakeholder Management and Communication - Act as a primary configuration lead in workshops with senior London-based business stakeholders. - Explain configuration design, rule logic, testing outcomes, issues, and trade-offs in clear business language. - Facilitate discussions between business SMEs, actuaries, developers, testers, architects, and delivery leads. - Provide structured status updates, risk/issue summaries, and decision points to project leadership. - Ensure business stakeholders understand how configured rules reflect their underwriting and pricing requirements. Testing, Validation, and Governance - Define and execute rule configuration testing, scenario testing, regression testing, and spreadsheet-to-Rulebook reconciliation. - Validate Rulebook outputs against source Excel models, expected pricing outcomes, underwriting rules, and edge-case scenarios. - Support SIT, UAT, defect triage, root-cause analysis, and defect resolution. - Maintain configuration documentation, traceability, version control, and audit evidence. - Ensure configurations support governance, auditability, and controlled deployment of pricing/underwriting changes. Technical Skills - Mandatory: - Strong Rulebook configuration mindset: ability to translate business rules into structured configuration. - Strong Excel skills, including ability to understand complex formulas, rating sheets, lookup tables, factors, and calculation flows. - Good understanding of XML and structured configuration files. - Ability to understand rule hierarchies, conditional logic, validations, decision trees, and calculation dependencies. - Experience with configuration testing, regression testing, and price-output reconciliation. - Familiarity with JIRA, Confluence, Azure DevOps, or similar delivery tools. - Ability to document configuration logic clearly. - Desirable: - Understanding of APIs, JSON, SQL, or data mapping. - Exposure to rating services, quote/bind platforms, broker portals, or delegated authority platforms. - Experience with document production, workflow configuration, or downstream integration. - Familiarity with rule deployment, release management, and environment promotion. Insurance Domain Knowledge - Insurance product structure - Submission, quote, bind, endorsement/MTA, renewal workflows - Rating factors, adjustments, deductibles/excesses, limits, commissions, taxes/fees where applicable - Underwriting appetite and referral logic - Authority limits and exception handling - Pricing model governance and audit trail - Deep actuarial expertise is not required, but the candidate must be able to understand pricing spreadsheets and hold credible conversations with pricing stakeholders.