Top Tech Jobs & Startup Jobs

Owns squad-level product definition, specifications, backlog prioritization, clarifications, validation intent, and delivery alignment for an AI-enabled, regulated B2B SaaS product. The role translates Product Management requirements into clear product behavior, workflows, constraints, and acceptance expectations while collaborating with Engineering, QA, UX, Support, customers, and stakeholders. It requires hands-on AI use for product work, understanding of Agentic AI fundamentals, strong product judgment, and the ability to operate autonomously in complex domains.

Leads commercial growth execution as the CCO’s operating partner, orchestrating go-to-market programs across Sales, Marketing, Customer Success, Partnerships, and Operations. Establishes execution frameworks, operating rhythms, accountability systems, KPI dashboards, and performance reporting. Aligns cross-functional leadership, scales sales motions, identifies capability gaps, removes execution barriers, and drives measurable revenue, customer, and market growth initiatives.

Owns consolidated financial reporting across Belgium, the UK, Poland, and the US. Responsibilities include preparing IFRS-compliant consolidated accounts and disclosure notes, reviewing balance sheet and P&L reconciliations, coordinating intercompany eliminations and FX translation, supporting statutory and group audits, and improving close and reporting processes using NetSuite, consolidation software, and AI-enabled tools.

Develop high-performance C++ software and Python tooling for clinical trial analytics. Translate statistical algorithms and research prototypes into scalable production software, optimize performance and memory usage, build automated tests, and support validation and deployment of computational models. Collaborate with researchers, statisticians, product managers, and engineers on data-intensive systems, architecture, automation, machine learning, and research innovation.

Explore, prototype, and productionize AI solutions for clinical data review, focusing on LLMs, agentic AI, RAG, and intelligent workflows. Build modular agent systems, APIs, and interfaces; integrate clinical data sources; evaluate and monitor AI performance; and ensure scalable, reproducible, traceable, auditable solutions aligned with regulatory expectations. Collaborate with clinical experts, product managers, and engineering teams while contributing to AI innovation strategy.