• Oversee technical direction for 32 microservices across 6 agile teams (~40 engineers). • Lead architecture and code reviews for Spring Boot and Ruby microservices. • Review and guide AWS Elastic Kubernetes Service (EKS) YAML configurations. • Improve health monitoring, DORA metrics, and operational observability. • Identify and recommend solutions to improve scalability, reliability, and availability. • Advise executives on strategic technology decisions and team capacity planning. • Oversee major deployments, high-risk secret key rotations, and on-call operations.

• Own the end-to-end technical onboarding of new Travel Pay clients, including corporate registration, Real Card Number (RCN) setup, and alias configuration. • Manage Custom Data Fields (up to 29 fields per template), MCC-based restrictions, purchase groups, and approval flows. • Prepare and submit Mastercard registration documentation, coordinate with Mastercard Implementation Managers, and manage boarding forms for VCN operations. • Serve as the first point of operational contact for product capability questions, providing structured, well-reasoned responses and supporting pre-sales configuration proposals. • Resolve operational incidents related to rejected VCNs, reconciliation mismatches between booking and transaction records, and enriched data configuration (Smart Data / CDF3). • Document SOPs and runbooks in Google Drive or similar tools to transition from ad-hoc tasks to a structured, scalable operational flow.

• Rapidly build and ship AI features that solve real customer and internal problems • Own projects end-to-end: from scoping and architecture to implementation and production deployment • Design, build, and deploy AI-powered features and applications from 0 to 1 in production • Integrate LLMs and AI models into existing products and workflows, handling the full stack from API integration to user-facing features • Build intelligent automation tools that improve internal operations, customer experience, or business processes • Create MVPs and prototypes quickly to validate ideas, then iterate based on real usage and feedback • Own the entire lifecycle: scoping, technical design, implementation, deployment, and monitoring • Build robust APIs and backend services that power AI features with proper authentication, rate limiting, and error handling • Design and implement data pipelines that support AI applications: document processing, embedding generation, vector search • Deploy and maintain containerized applications on AWS infrastructure (ECS, Lambda, S3, RDS)

• You will play a key role in designing, developing, and documenting mechanical & plumbing systems for a variety of projects. • Close coordination with architects, interior designers, and engineering consultants. • Strong grasp of mechanical and plumbing design concepts is required. • Collaborate with internal members of the mechanical & plumbing design team.