Top Tech Jobs & Startup Jobs

Build, deploy, and operate Java/Spring Boot backend services in a cloud-native microservices architecture. Develop APIs with gRPC/Protobuf and REST, work with PostgreSQL, contribute to Kafka-based event-driven features, use AWS services, write automated tests, review code, and validate AI-generated code. Collaborate with senior engineers, product teams, U.S. leadership, and Spanish-speaking stakeholders to deliver software independently.

Own full-stack features from Java and Spring Boot microservices through React and Next.js interfaces. Design APIs, data models, service boundaries, and event-driven systems; operate services on AWS; write automated tests; review code; mentor engineers; and establish technical standards. Collaborate with US-based leadership and Spanish-speaking Latin American stakeholders to translate requirements into production features, using AI coding tools with strong validation and engineering judgment.

Lead functional quality assurance for software products, defining testing strategies and executing manual, regression, integration, exploratory, cross-browser, security, and UAT testing. Collaborate with software engineers and Agile teams, create test data and defect metrics, support production implementations, validate user stories, and use TFS or Jira for test management. Mentor quality analysts, research testing tools and practices, and apply SQL, web-service testing, and database skills.

Leads end-to-end delivery and customer implementation of a mobile e-commerce platform across Latin America. Manages timelines, dependencies, risks, priorities, stakeholder alignment, executive communications, and cross-functional collaboration across engineering, product, business, and customer teams. Supports onboarding, adoption, and ongoing product evolution while balancing competing priorities and maintaining the long-term product vision. Requires extensive project management experience, fluent Spanish, professional English, and strong customer-facing leadership skills.

Design, build, and operate secure, production-grade AI applications, workflow automation, APIs, data pipelines, integrations, reusable solution accelerators, and observability tooling. The role partners across Marketing, Sales, PMO, GTM, Delivery, and Operations to reduce manual work and improve efficiency. Responsibilities include event-driven application development, LLM and RAG implementations, database and ETL work, AWS cloud development, API design, security, and automated testing.

Test Dynamics 365 CRM customizations by creating scenarios, writing and executing automated and manual tests, logging defects, and supporting production implementations. Collaborate on testing strategy, participate in Agile ceremonies, use Azure DevOps to manage test cases, and work with developers to ensure quality, automation, and integration across systems.

Build and enhance an exam development platform using Angular front-end and C# backend. Collaborate with product and design teams, ensure performance and responsive UX, follow CI/CD and automated testing best practices, perform code reviews, troubleshoot issues, mentor junior developers, and incorporate improvements including AI/ML retrieval-based solutions.

Design, build, and optimize growth-focused product features and experiments (A/B tests) to improve acquisition, activation, engagement, retention, and monetization. Instrument analytics, analyze funnels and user behavior, improve onboarding and conversion paths, optimize performance and SEO, and build internal tools to support marketing, sales, and growth operations. Collaborate with Product, Marketing, Design, and Engineering and report on experiment outcomes and growth KPIs.

Design, build, and operate standardized CI/CD platforms across AWS and on‑premises; implement progressive delivery (feature flags, canary, blue/green), automated testing, DB migrations and masking, observability, security-by-design, secrets management, and platform standardization to enable reliable, auditable releases across environments.

Design and deliver scalable data platforms and pipelines, enable data science teams, and implement best practices in automation and governance.