ArisInfra

India
200 Total Employees
Year Founded: 2021

Jobs at ArisInfra

Let Your Resume Do The Work
Upload your resume to be matched with jobs you're a great fit for.

Recently posted jobs

YesterdaySaved
In-Office
Bangalore, Bengaluru Urban, Karnataka, IND
eCommerce • Logistics • Software • Industrial
Lead ArisInfra’s engineering strategy, organization scaling, platform re-architecture, cloud-native infrastructure, AI integration, and product delivery. Responsibilities include modernizing backend and frontend systems, building scalable and resilient architectures, establishing DevOps and reliability practices, deploying ML capabilities, partnering with executives, and hiring and developing engineering leaders.
YesterdaySaved
In-Office
Bangalore, Bengaluru Urban, Karnataka, IND
eCommerce • Logistics • Software • Industrial
Build and operate scalable backend services for logistics, credit, compliance, and AI-driven applications. Responsibilities include designing high-throughput APIs and workflows, developing distributed and real-time systems, making data and reliability decisions, implementing testing and monitoring, and owning production services through deployment and debugging.
YesterdaySaved
In-Office
Bangalore, Bengaluru Urban, Karnataka, IND
eCommerce • Logistics • Software • Industrial
Senior hands-on backend engineer responsible for designing, implementing, and operating scalable production systems for logistics, credit, compliance, AI, and real-time tracking. The role leads complex feature development, contributes to architecture and reliability decisions, mentors engineers, improves performance and observability, and owns services throughout their production lifecycle.
YesterdaySaved
In-Office
Bangalore, Bengaluru Urban, Karnataka, IND
eCommerce • Logistics • Software • Industrial
Design and build scalable backend microservices, distributed systems, event-driven architectures, data pipelines, and real-time analytics for procurement, logistics, credit, and compliance. Lead cloud infrastructure, CI/CD, observability, security, performance tuning, and reliability initiatives across high-throughput systems. Apply machine learning and automation to vendor recommendations, demand forecasting, risk scoring, and fraud detection while driving engineering standards through code reviews and cross-functional collaboration.