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Plan, conceptualize, and implement software implementation projects; conduct workshops and user trainings on-site or online, ensuring correct application of our software. Document processes in the CRM and support sales with presentations and events to drive growth.

Design and deliver scalable, highly available cloud-based infrastructure and collaborate with cross-functional teams to ship features. Ensure performance, quality, and security of applications and infrastructure, identify bottlenecks, and participate in code reviews.

Lead the multi-cloud DevOps and data strategy as the technical owner of infrastructure, designing, building, and operating key systems while guiding the infrastructure evolution to scale for Fortune 500 customers.

Lead backend work to scale services across cloud and hybrid deployments, owning core components. Collaborate with product and design to deliver features end-to-end and champion thorough testing.

Lead and mentor engineers, contribute hands-on to architecture, and drive scalable, high-quality software at PlanCraft. Partner with cross-functional teams to shape engineering practices and enable fast delivery.

Design, build, and maintain APIs, services, and other backend systems across Visable engineering teams. Debug production issues and help implement large-scale features while upholding engineering standards.

Architect and develop robust Python-based frameworks for robotic data pipelines from collection to processing and access. Design modular microservice architectures to support scalable, maintainable data workflows and reliable APIs across components.

Develop robust backend components and well-structured APIs using Go and concurrency patterns. Work with SQL and NoSQL databases, CI/CD pipelines, and Docker to deploy scalable, observable services.

Support the resolution of production issues in cloud-native environments and contribute to hotfix image releases. Improve observability, monitoring, CI/CD pipelines, and automated testing; support Kubernetes-based deployments and collaborate with L2 support, QA, and R&D.

Design, integrate, and operate robotic systems using ML models under real-world constraints such as latency and safety. Collaborate with ML researchers to ensure reliable, real-world performance of AI-driven robotics.