Top Tech Jobs & Startup Jobs

Own a 0-to-1 product surface end-to-end, including vision, roadmap, specifications, shipping, metrics, and customer outcomes. Partner directly with customers on discovery, onboarding, growth reviews, and deployments. Collaborate with software, ML/AI, and data engineers on data pipelines, models, agents, and activation platforms. Prioritize customer requests, define measurable success criteria, and guide product decisions across teams and time zones.

Own sourcing and recruiting across LATAM markets, including Mexico, Brazil, Colombia, Argentina, Peru, and Chile. Build talent maps and pipelines for technical and non-technical roles, engage passive candidates, conduct recruiter screens, partner with hiring managers, track funnel performance, and improve recruiting processes. The role requires resourcefulness, urgency, strong market research skills, and professional fluency in English and Spanish.

Lead enterprise data deployments across Latin America, integrating customer data into ClickHouse or warehouse-native Snowflake and BigQuery environments. Build orchestration pipelines, canonical data models, semantic layers, and AI-assisted discovery workflows. Partner directly with customer data teams, resolve complex integration challenges, optimize performance, and establish the region’s deployment playbook. Professional English and Spanish fluency are required, with regular customer travel and potential future relocation within Latin America.

Build and operate production-grade agentic AI systems, owning agent evaluation, testing, retrieval, orchestration, monitoring, and production reliability. Design workflows with LangChain or LangGraph, create evaluation harnesses and regression gates, diagnose failures, optimize latency and cost, and establish technical standards. The role requires 6+ years of software engineering experience, including 2+ years building production LLM or agent systems, plus strong ownership and communication in an ambiguous startup environment.

Build and operate production-grade agentic AI systems, owning evaluation harnesses, metrics, regression gates, retrieval, orchestration, monitoring, and production reliability. Diagnose failures such as hallucinations, tool misuse, and retrieval misses, turning them into durable fixes. The role requires designing LangChain or LangGraph workflows, optimizing accuracy, latency, and cost, integrating external platforms, and collaborating clearly in a fast-moving startup environment.

Build Hilbert’s enterprise presence across major U.S. consumer markets by identifying target accounts, generating pipeline, opening executive relationships, and managing complex sales cycles through close. The role requires translating AI, data, and analytics capabilities into measurable growth outcomes, navigating technical and business stakeholders, developing strategic business cases, and turning early wins into repeatable sales motions. This is a hands-on market-building role with potential for expanded leadership scope.

Own Hilbert’s marketing channels and growth execution, including LinkedIn, founder communications, blog, newsletter, SEO/AEO, videocast distribution, events, community, landing pages, lifecycle nurture, and conversion measurement. Build channels from zero, repurpose customer evidence into content, test new distribution opportunities, create AI-enabled systems, and measure account engagement and qualified meetings rather than vanity metrics.

Build and lead Hilbert’s global privacy program across US, UK, and EU jurisdictions. Advise product and engineering on privacy-by-design for agentic AI workflows, negotiate enterprise contracts and DPAs, manage international data transfers and subprocessors, and support security incident response. Serve as the primary legal contact for enterprise customers while providing general commercial and product counsel in a fast-moving startup environment.

Build and deploy hybrid data integrations for enterprise customers: implement ClickHouse or warehouse-native pipelines (Snowpark/BigQuery), construct AI semantic layers and canonical growth models, partner with AI discovery agents to accelerate onboarding, and lead technical enterprise deployments ensuring performance and reasoning consistency.

Build and own end-to-end product surfaces for an AI agent: frontend React dashboards, backend agentic query engines, enterprise-ready services, admin tools, and integrations. Collaborate with Product and ML teams to design, ship, and operate scalable, secure, configurable systems.