Top Tech Jobs & Startup Jobs

Own the vision, strategy, roadmap, and lifecycle of a shared lending platform serving multiple products and markets. Define platform architecture principles, APIs, configuration capabilities, and build-versus-buy decisions. Lead real-time credit decisioning, risk and compliance integrations, data aggregation, IFRS9 reporting, and ML-assisted lending capabilities. Coordinate dependencies across lending products and collaborate with Credit Risk, Analytics, Engineering, Compliance, and country business teams.

Build and own AI-first financial products across the full lifecycle, from requirements and system design through deployment, testing, and operations. Develop scalable backend systems primarily with Java and AWS, integrate frontend and portal experiences, apply agentic coding and prompt engineering, validate product assumptions with customers and data, and continuously improve solutions through rapid experimentation.

Own product analytics for Product-Led Growth pods across banking apps in the Philippines and South Africa. Analyze adoption funnels, cohorts, retention, customer behavior, and experiment results; guide A/B and multivariate testing; define instrumentation and event taxonomies; validate data quality; build decision-focused dashboards; and partner with product, engineering, design, marketing, and country teams to turn insights into roadmap actions.

Build and operate the backend financial core for a stablecoin and digital-assets wallet. Responsibilities include developing an event-sourced double-entry ledger, posting and transaction-processing flows, reconciliation controls, audit trails, financial projections, and operational repair workflows. The role requires strong database and distributed-systems expertise, including idempotency, event ordering, concurrency control, schema evolution, recovery, and production support. The engineer will collaborate with finance, treasury, risk, compliance, operations, and engineering teams.

Owns CI/CD pipelines and infrastructure-as-code for a Databricks-based Data as a Product platform on AWS. Responsibilities include automating deployments, managing environments with Terraform and GitOps, provisioning AWS resources, integrating Datadog and AI tooling, implementing monitoring and alerting, tracking DORA metrics, and improving platform reliability and developer experience. The role partners closely with data engineering and platform teams to create self-service, code-first workflows.

Analyzes credit, bureau, transactional, and repayment data to identify risk drivers and improve lending decisions. Builds credit risk features and predictive model inputs, supports policy experimentation, monitors model and feature performance, and conducts portfolio analytics such as vintage, roll-rate, collections, and loss-driver analysis. Collaborates with engineering and data teams on quality, lineage, reproducible pipelines, governance, and production-ready documentation.

Lead and grow engineering teams responsible for authentication and authorization architecture. Own product lifecycles from design through deployment and optimization, shape technical roadmaps, guide scalable and secure architecture, review technical proposals, and remain initially 40–50% hands-on. Drive cross-functional collaboration, delivery of complex initiatives, process improvement, mentoring, and organizational scaling in a high-growth environment.

Design, develop, test, deploy, monitor, and improve scalable backend services for a digital banking platform. Responsibilities include solving complex technical problems, designing distributed systems, documenting requirements, collaborating in Agile and DevOps teams, and owning features throughout their lifecycle. The role emphasizes high availability, low latency, database design, microservices, event-driven architecture, and cloud deployment.

Designs, develops, tests, deploys, and monitors Databricks data pipelines on AWS using PySpark and SQL. Builds scalable data solutions, quality dashboards, lineage and monitoring tools, supports legacy-system migrations, and enforces data security, retention, privacy, governance, and development best practices.

Analyze data from multiple sources, build reliable datasets and reports, validate data quality, and apply statistical techniques to identify trends. Partner with stakeholders across marketing, operations, finance, and product to deliver actionable insights. Create dashboards, KPI tracking tools, and experiments; communicate findings to technical and non-technical audiences. Promote data literacy, document best practices, and support company-wide analytics initiatives.