**Head of Cloud Platform** **About HYPR** HYPR is a technology company at the intersection of AI, data and location intelligence. It operates a proprietary end\-to\-end platform that connects physical\-world behavior, offline transactions, mobile signals and omnichannel media execution. R$100M\+ annual revenue, bootstrapped and profitable, category leader in physical retail media and incrementality measurement in Brazil. Privacy by design: no personally identifiable data is collected anywhere in the platform. **What we have built** * **Groundflow** : transactional data infrastructure built on fiscal receipts. Over 350 million receipts and 1 billion\+ SKUs observed in real physical retail transactions, R$3\.16 trillion in GMV processed, 25 million new receipts a month, from the largest chains to the long tail, granular to the SKU. * **Places Graph** : the geospatial layer that turns coordinates, visits and store identity into location intelligence. * **The IQ suite** : geoIQ, revIQ, bidIQ, adsIQ and askIQ, the applications our clients use for measurement, optimization, activation and research. All of them run on four data pipelines: places, transactions, audiences and performance. * **Demandshift** : predictive demand analytics by product, launched in September 2026\. Models demand across 500\+ product categories in FMCG, auto, real estate and upscale retail on top of the full receipt base. * **Swarm** : an agentic workspace where a brand opens a case in one sentence and a system of AI agents breaks it into hypotheses, investigates them in parallel across the four pipelines, has an independent auditor redo the numbers, and returns ranked hypotheses with confidence levels and actions ready to execute. * **HYPR Audiences** : our audience catalog exposed as a public MCP server and plugin, available to agencies and advertisers inside their own AI tools. **The platform** HYPR Cloud is where all of this runs: where data is ingested, models are trained, agents reason, decisions are made and products are delivered at scale. It is a hybrid architecture (public cloud plus owned infrastructure for the receipt flow), a vendor\-agnostic AI layer that uses more than one foundation model provider by use case, and a modern orchestrated data stack. It is the technical foundation of HYPR’s long\-term differentiation. **The role** You own HYPR Cloud end to end: architecture, development and operation of the data, AI and agent systems that directly support strategy, revenue and competitive advantage. The role reports to the CEO and works directly with the board. It is designed for a founder\-grade technical leader: deep enough to design systems personally, with the judgment for high\-impact long\-term decisions and the credibility to operate as a peer to executive leadership. This is not a research role, a purely managerial role, or a place to build a large organization. It is a build\-and\-own mandate. **Mission** Design, build and scale AI\-native platforms that turn HYPR’s proprietary data advantage into defensible, monetizable systems, from receipt ingestion to predictive models to autonomous agents, with world\-class engineering standards, execution speed and economic discipline. **What you will own** * HYPR Cloud architecture: data pipelines, ML and LLM systems, agent orchestration, APIs, production systems * The evolution of Groundflow, Places Graph, Demandshift and Swarm as a single coherent platform * Technical strategy aligned with board objectives and long\-term direction * Reliability, scalability, performance and cost efficiency of every production system * Hiring, development and leadership of a small, senior engineering team * Translation of ambiguous, high\-impact business problems into production\-grade systems * Technical risk and architectural integrity at scale **How you will drive impact** * Define and evolve the architecture for AI\-native adtech, demand\-prediction and location\-intelligence platforms * Take predictive models (Demandshift) and agent systems (Swarm) from working product to platform: evaluation, cost per answer, auditability, reliability * Lead the productionization of AI models (LLMs, proprietary models, hybrid systems) embedded in decision workflows * Integrate foundation models with structured, geospatial, transactional and mobile data at SKU and store granularity * Build and operate high\-throughput, low\-latency pipelines for real\-time and batch decisioning * Set engineering standards for quality, security, privacy, observability, MLOps and reliability * Make build\-vs\-buy, stack, model\-provider and cloud economics decisions with long\-term leverage in mind * Partner with the CEO and the board on platform strategy and technical bets * Keep execution velocity high while preventing uncontrolled technical debt * Ensure systems are economically efficient, not just technically sophisticated **Leadership expectations** * Direct involvement in architecture, system design and critical techn