QA Engineer- R01570602
The QA Engineer will identify software weaknesses, create and execute test cases, and maintain automation suites. They will also collaborate with cross-functional teams to resolve bugs and ensure timely project delivery.
The QA Engineer will identify software weaknesses, create and execute test cases, and maintain automation suites. They will also collaborate with cross-functional teams to resolve bugs and ensure timely project delivery.
Design and maintain CI/CD pipelines, container platforms, infrastructure automation, and AWS environments, while supporting reliability, monitoring, and cloud migrations. Collaborate with application and architecture teams to deliver secure, compliant, scalable, and cost-effective solutions.
The Architect will design and scale enterprise-grade AI agents, autonomous workflows, and LLM-powered applications. They are responsible for defining reference architectures and integrating AI solutions across various business functions.
The developer will gather and document business requirements for NetSuite enhancements while partnering with finance and operations stakeholders. They are also responsible for configuring system features, managing user acceptance testing, and resolving issues to ensure optimal system performance.
The Lead Systems Engineer will design, implement, and optimize cloud-based contact center solutions using Amazon Connect for healthcare environments. This role involves leading technical delivery, managing integrations, and ensuring regulatory compliance while supporting high-volume operational workflows.
Design and implement advanced pricing customizations and configure Apttus CPQ modules to streamline quoting and sales processes. Troubleshoot technical issues and conduct system testing to ensure optimal performance and user adoption.
Engage with business stakeholders to identify high-value AI opportunities and design full-stack AI prototypes that solve complex healthcare operational problems. Partner with governance teams to harden these prototypes into production-grade, enterprise-ready systems while maintaining clear communication with executive leadership.
Engage with business stakeholders to identify and design high-value AI solutions that address complex healthcare operational challenges. Develop and deploy full-stack AI prototypes and production-grade applications while ensuring compliance with governance and regulatory standards.
Lead the design and implementation of enterprise-scale Data and AI platforms, focusing on scalable architectures and governance. Drive the adoption of Generative AI and Agentic AI solutions to modernize business capabilities.
Design and implement robust statistical models and machine learning algorithms for large-scale predictive analytics. Lead end-to-end data science projects and mentor junior scientists to drive measurable business impact.
The role involves discovering high-value AI opportunities within healthcare operations and designing end-to-end AI prototypes. You will be responsible for scaling these solutions into production-grade systems while engaging directly with executive stakeholders.
Lead large-scale digital transformation initiatives focusing on cloud migration, application modernization, and SaaS enablement. Act as a strategic advisor to executive leadership while governing enterprise architecture frameworks and standards.
The Lead AI Engineer is responsible for designing, implementing, and productionizing scalable AI and computer vision solutions on Microsoft Azure. They will also define engineering best practices, mentor team members, and ensure the reliability and performance of AI services.
The Senior Data Scientist will develop and deploy advanced machine learning and computer vision solutions using Azure. They will collaborate with data engineers to build scalable pipelines and communicate insights to stakeholders.
The Fullstack Engineer will build, design, and maintain robust web applications using Node.js or Python for the backend and React for the frontend. They will also develop and enhance RESTful APIs and microservices to ensure seamless integration with other systems.