Top Tech Jobs & Startup Jobs

Develop and maintain applications in Java, analyze requirements, implement changes, and produce technical documentation while collaborating in an Agile team.

Manage end-to-end recruitment lifecycle for IT positions, source candidates, partner with hiring managers, and maintain candidate experience.

Lead and govern large-scale testing programs: define testing strategy, plan and supervise functional and non-functional testing, manage schedules/resources/reporting, validate deliverables, coordinate QA stakeholders, and drive continuous improvement of testing practices.

Design and implement automated testing frameworks and reusable components; develop UI, API, and data-driven test suites; integrate tests into CI/CD; improve coverage and execution efficiency; review and coach teammates; contribute automation best practices and support quality engineering across projects.

Define test approaches and scope, design and run functional, integration and regression tests, prepare test scenarios/data, coordinate with development, analyze defects, support UAT and release validation, and improve testing practices.

Lead incident management and root cause analysis for mission-critical services; define monitoring and performance baselines; support deployments, operational readiness and cross-team troubleshooting; contribute to automation, produce operational reports and recommend improvements.

Design, develop and maintain enterprise software and integrations. Build reusable microservices, implement unit and integration tests, participate in architecture and code reviews, produce technical documentation, and mentor junior developers while following Agile and modern engineering practices.

Lead and coordinate software development, maintenance and operational support; define scope, timelines and resources; manage Agile teams; monitor risks, budget and quality; coordinate stakeholders; ensure compliance with PM methodologies and security; produce management reports and drive continuous improvement.

Lead design, deployment, and operation of large-scale Elasticsearch search and data platforms. Architect ingestion pipelines, observability, and integrations; deploy cloud-native workloads on Azure/AWS with Kubernetes and IaC; ensure performance, security, and reliability; mentor teams and drive engineering standards.

Design, build, and operate production-grade data and ML pipelines: ETL/ELT, model packaging and serving, CI/CD, containerized deployments, monitoring, infrastructure-as-code, and collaboration with data scientists to put ML prototypes into scalable, secure production services.