Top Remote Jobs in Lisbon

Own full-cycle technical recruiting across Engineering, Product, and Design. Build diverse talent pipelines, advise hiring managers and senior leaders, use AI-assisted recruiting tools, improve recruiting processes, manage talent communities, and report on hiring metrics. The role emphasizes stakeholder influence, candidate advocacy, sourcing hard-to-find talent, and delivering strong candidate and hiring-manager experiences.

Own product and protocol security across Jito’s Solana-based products. Responsibilities include threat modeling, secure design and code reviews, deployment hardening, internal audits, onchain monitoring, bug bounty operations, remediation tracking, AI-assisted security testing, and key and asset risk management. The role requires production software engineering experience, strong application security expertise, security automation skills, and familiarity with Web3, crypto, or DeFi.

Develop and deploy machine learning and data science solutions for mission planning, situational awareness, workflow automation, predictive modeling, and operational decision support. Process multimodal datasets including drone sensor, geospatial, time-series, text, and unstructured data. Build, evaluate, optimize, document, and productionize models while collaborating with engineering, product, and domain teams. Apply classical machine learning, deep learning, language models, and AI ethics practices across the full data science lifecycle.

Own the full sales cycle for mid-market customers, from self-sourced outbound prospecting through discovery, product demonstrations, negotiation, and closing. Build multi-stakeholder consensus, develop business cases, manage security and procurement reviews, sell web app and API use cases, maintain accurate CRM data, and partner with growth, product, customer success, and PLG teams to expand adoption of HeyGen’s AI video platform.

Own a portfolio of international B2B software customers from contract signature through onboarding, go-live, hypercare, and steady state. Lead customer implementation projects, integrations, configuration workshops, cross-functional rollouts, adoption initiatives, and L2+ support. Coordinate customers, engineering, product, partners, and suppliers while managing timelines, risks, feedback, renewals, and expansion signals. Help standardize and automate customer operations using AI tools.

Lead platform engineering across infrastructure, CI/CD, testing, developer tooling, observability, and secure software delivery. Build internal platforms, golden paths, and shared tooling that improve developer and AI-agent productivity. Establish engineering standards, integrate security controls into pipelines, shape repositories for coding agents, and measure impact through DORA metrics and engineering feedback.

Responsible for end-to-end financial accounting and compliance across multiple markets, including month-end close, reconciliations, statutory reporting, tax compliance, audit support, intercompany accounting, and financial reporting. The role partners with finance teams and external advisors, maintains balance sheet integrity, supports process improvements and automation, and contributes to finance transformation initiatives.

Own retention strategy, revenue targets, and lifecycle roadmaps for complex Shopify brand accounts. Manage client relationships, develop advanced campaigns, interpret performance data, lead onboarding, review work, and mentor junior retention managers and marketers. The role focuses on high-value account strategy, full-funnel retention, client leadership, and continuous improvement in lifecycle marketing.

Develop and maintain scalable Python backend systems, design microservices architectures, deploy cloud applications on AWS, and manage Kubernetes-based containerized environments. Optimize performance, reliability, and security while troubleshooting complex issues. Collaborate with product managers and engineering teams on architecture and technical strategy. Requires extensive backend development experience, AWS and Kubernetes expertise, database knowledge, and strong debugging skills. Familiarity with CI/CD, Docker, and DevOps practices is preferred.

Develop machine learning and analytics solutions using large-scale datasets. Responsibilities include feature engineering, predictive modeling, workflow optimization, customer implementations, production deployments, stakeholder collaboration, technical training, and resolving data-related challenges. The role requires Python, PySpark, machine learning pipelines, MLflow or Airflow, statistical modeling, and strong communication skills, with preferred experience in fraud detection, risk analytics, compliance, cloud environments, and model monitoring.