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.
The Product Owner defines the product vision and manages the backlog to deliver high-value features aligned with business goals. They act as a bridge between stakeholders and engineering teams to translate business needs into actionable user stories within an Agile framework.
The Lead Data Engineer will build state-of-the-art pipelines and data models using Databricks and Azure Synapse to support studio decision-making. They will develop large-scale lakehouse and warehouse analytics systems processing both real-time and batch data feeds.
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 role involves driving the adoption and industrialization of AI tooling and agent workflows across engineering teams. You will collaborate with Microsoft AI specialists to build prompts and agents while embedding within Scrum teams to accelerate SDLC productivity.
Design, develop, and maintain end-to-end full stack solutions for a mission-critical enterprise payments platform using Java and React. Collaborate with cross-functional teams to ensure high availability, performance, and security of payment processing systems.
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.
