Partner with sales and leadership to position Complexio’s technology in client meetings, discovery calls, and solution workshops
Understand client business processes and map those to the platform’s capabilities (ingestion, mapping, knowledge graph, orchestration, agent workflows)
Define and document the scope of PoCs, pilot programs, and commercial deployments
Articulate technical concepts (data architecture, infrastructure, security) in commercially relevant language for executive stakeholders
Assist in the development of proposals, technical diagrams, SoWs, and integration outlines
Work closely with engineering to ensure solution feasibility and clarity during the sales cycle
Tailor demos and walkthroughs using real or anonymised data to showcase applied use cases (e.g. lost invoice detection, regulatory process mapping)
Support conversations on deployment models (on-prem, air-gapped, hybrid) and data governance
Help refine pricing estimates based on use case complexity and integration requirements
Trusted by the sales team and Co-CEO to support key deals and strategic conversations
Confidently handles technical Q&A with both IT leaders and business users
Accelerates sales cycles by reducing friction around deployment, data access, and technical feasibility
Wins customer confidence through clarity, responsiveness, and commercial empathy
Requirements
5+ years in a customer-facing technical role (pre-sales, solutions architecture, sales engineering)
Experience working alongside commercial or executive teams to position complex platforms
Deep understanding of enterprise data environments — familiarity with APIs, cloud infrastructure (AWS/Azure), IAM, and integration models
Strong communication skills — equally comfortable with CIOs, compliance heads, and data architects
Structured, proactive, and persuasive — able to distil core value from complex systems
Preferred: Background in AI, machine learning, data platforms, or graph technology
Preferred: Experience in regulated industries (shipping, energy, finance, supply chain)
Preferred: Ability to adapt commercial materials and pitch narratives to different personas
Preferred: Familiarity with privacy-preserving architectures, unstructured data processing, or event-based reasoning models