In this role, you will deploy and scale a next-generation AI platform that connects strategy to execution through advanced analytics and machine learning. You will work at the intersection of software engineering and infrastructure, ensuring that AI capabilities are effectively integrated into real-world environments. Your responsibilities will include managing the platform delivery lifecycle and collaborating with various technical stakeholders to drive successful deployments. This position offers an opportunity to contribute to a culture of continuous learning and innovation within a global community.

• Bachelor's or Master's degree in computer science, machine learning, applied statistics, mathematics, engineering, artificial intelligence, or a related field
• 4+ years of hands-on experience as a Software or Platform Engineer, with exposure to enterprise platform deployments
• Strong engineering fundamentals with proficiency in Python and familiarity with modern full-stack development
• Experience designing, deploying, and managing cloud-based systems, including containerization and orchestration frameworks
• Deep expertise in Kubernetes cluster architecture, installation, configuration, and lifecycle management at production scale
• Experience with CI/CD pipelines and Infrastructure as Code tools
• Strong understanding of data architectures and platform design, including relational and graph databases
• Familiarity with AI platform concepts is a plus
• Strong problem-solving skills with a structured approach to debugging
• Experience with DevSecOps and infrastructure security practices is a plus
• Willingness to travel
• Ability to communicate effectively with technical and non-technical stakeholders

• Deploy and configure production-grade systems across cloud and hybrid infrastructures
• Validate performance and stability of deployed systems
• Ensure structured handovers for long-term success
• Troubleshoot issues end-to-end and ensure platforms are production-ready
• Contribute to deployment tooling, automation, and product feedback loops
• Collaborate with engineers, product teams, and technical experts on interdisciplinary initiatives
• Document patterns and refine delivery practices for team knowledge-sharing
• Guide adoption through practical best practices
• Support continuous evolution of AI technology through feedback loops

• Employees at McKinsey are often offered a comprehensive benefits package, including medical, dental, and vision coverage, prescription benefits, mental-health resources, expert medical opinions, and travel emergency protection. Financial benefits typically include retirement contributions and savings plans, life/accident/disability insurance, tax-advantaged accounts, and financial coaching. Many roles also feature generous paid time off (including volunteering days), flexible/hybrid work options, family care support (parental leave, fertility/adoption/surrogacy assistance, backup care), tuition reimbursement, transportation benefits, discounts, and matching gifts.