Top Tech Jobs & Startup Jobs

Lead corporate development and strategic partnership initiatives, including acquisitions, investments, and transactions. Build financial models, conduct valuation and due diligence, analyze fintech markets, support negotiations and integration, and provide strategic recommendations to executives and the Board. Collaborate with business, finance, accounting, and legal teams while managing multiple priorities and leveraging AI tools to improve M&A and analytical efficiency.

Own the vision, roadmap, business outcomes, and go-to-market strategy for Remitly’s AI-powered conversational experiences. Lead cross-functional teams to scale chat-based remittance journeys, launch integrations with platforms such as ChatGPT and Claude, optimize product-led growth funnels, and use research, experimentation, analytics, and AI quality metrics to improve conversion, retention, engagement, customer satisfaction, and cost-to-serve.

Lead full‑stack design and delivery of customer‑facing web and mobile features across frontend and backend systems. Own architecture, ship reliable and observable services, mentor engineers, drive process and cross‑team designs, participate in on‑call rotation, and collaborate with product, design, and analytics.

As an AI Native Software Engineer, you'll build products using AI coding agents, translating customer needs into solutions, and ensuring quality delivery and documentation.

As an Agentic Software Engineer, you'll build and deploy production-grade AI systems, reverse-engineer existing software, guide teams, and facilitate customer discovery.

As a Forward Deployed Engineer at Remitly, you will leverage AI agents to build applications, translate customer needs, and evaluate outputs for quality and security, focusing on delivery speed and robustness.

Build a zero-to-one fullstack product for Remitly Business, design secure scalable frontend and backend systems, set technical standards, lead and decompose team projects, mentor engineers, ensure reliability and observability, and collaborate cross-functionally. Hybrid role based in Seattle.

Lead design, implementation, and scaling of end-to-end ML systems including feature pipelines, model training, evaluation, deployment, and monitoring. Partner with cross-functional teams to productionize models, apply MLOps best practices (automated retraining, CI/CD, drift detection), and mentor engineers to maintain high code and system quality.

Lead product analytics for new financial product initiatives: build business models, segment customers, create datamarts and dashboards, ensure data quality, design experiments, and surface insights using AI-enabled tooling to guide product decisions.

Design, build, and productionize real-time fraud detection models. Advance adversarial-domain techniques (graph, sequence, anomaly detection), design robust evaluation for biased/delayed labels, ensure low-latency reliable deployment, monitor models in production, and collaborate with data scientists and stakeholders to translate fraud signals into modeling solutions.