Top Tech Jobs & Startup Jobs

Design, develop, and maintain scalable automated test frameworks and scripts (UI, API, backend). Integrate tests into CI/CD, analyze results, debug failures, monitor deployments, improve coverage, and mentor junior QA engineers.

As a Senior AIOps Engineer, you will lead the transformation of IT operations by implementing AI, ML, big data analytics, and RPA solutions to enhance operational efficiency and innovation.

Lead and grow a skilled AIOps engineering team, driving AI-powered solutions for operational optimization and business value, while fostering collaboration and continuous learning.

Lead MAS Major Payment Institution license applications for DPT and SCS services, manage MAS engagement, implement MAS Stablecoin Framework compliance, oversee AML/CFT, CDD/EDD, reserve asset management, redemption mechanisms, audits, and TRM coordination with IT and exec leadership.

The Senior Machine Learning Engineer at Razer will develop machine learning models, optimize solutions for scalability, and collaborate with cross-functional teams while addressing ethical considerations.

Responsible for ensuring quality assurance of mobile apps on Android and iOS platforms, designing and executing test cases, and collaborating with developers to resolve defects within an Agile development process.

Manage and optimize cloud-hosted databases (MySQL, Aurora, MongoDB, MSSQL, PostgreSQL, DynamoDB) on AWS and MongoDB Atlas; implement backups, security, automation (Terraform, CloudFormation, Lambda), monitoring, disaster recovery, migrations, performance tuning, and collaborate with development teams.

Manage full-cycle accounts payable: code, review, and process invoices; run vendor and employee payment cycles; review AMEX expenses in Coupa; set up vendors in SAP; prepare month-end accruals and 1099s; respond to vendor/employee inquiries; support audits, UAT, and process improvements.

Develop and implement computer vision algorithms, evaluate model performance, and integrate solutions into larger systems, while maintaining documentation and staying updated on technology advances.

Design, develop, and deploy AI solutions by integrating ML models, optimizing workflows, and collaborating across teams. Ensure performance and security in production environments.