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Tier-1 brand, metro Bangalore, and a popular senior cloud engineering role drive high competition.
Deep cloud platform, distributed systems, and Java/Kubernetes expertise limits transferability across industries.
Explicit 8+ years plus mandatory Java, distributed systems, Kubernetes and cloud experience enforces strict filters.
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Architect, design, implement, and operate complex PaaS for GPU cloud services focused on Deep Learning and AI.
Lead technology stack decisions and implementation methodology for large-scale distributed GPU cloud platforms.
Collaborate cross-functionally with partners, UX/UI designers, and front-end teams; drive test automation and CI/CD practices.
8+ years of hands-on experience building complex microservices and large-scale distributed cloud services.
Strong expertise in Java (including Collections API, Streams API, Concurrency, I/O), OOP concepts, design patterns, and back-end system architecture.
Experience with databases including RDBMS and NoSQL (Cassandra, DynamoDb, Redis).
Experience managing Kubernetes clusters, implementing monitoring/logging (e.g. Prometheus, Datadog, Splunk), and embedding DevSecOps in CI/CD pipelines.
Proficient in multiple backend and cloud technologies such as Java Springboot, Golang, Kubernetes, Docker, and cloud providers (AWS, GCP, Azure).
Experienced supporting high-availability, resilience, observability, and production incident diagnosis in dynamic, complex cloud environments.
Capable of mentoring others and driving technical excellence while balancing speed, quality, and simplification in product delivery.