Associate Architect

Role:Associate Architect - Platform Experience Required:6 to 9 years Location:HyderabadJob Summary: Join our dynamic team as aPlatform Architectand leverage your expertise in production-scale platforms within theGenAI or ML domain . In this role, you'll be instrumental in designing, developing and maintaining cutting-edge build and test environments for critical GenAI workloads running on foundational cloud infrastructure. You'll partner with architects to design and implement highly robust and scalable systems, while also providing crucial development support to SRE/Operations teams as they tackle complex distributed systems challenges at scale. We're seeking an engineer who champions Quantiphi's dedication toCloud-Native development , with a particular emphasis onKubernetes .What You’ll Be Doing: As aPlatform Architect , you will play a pivotal role in designing, implementing, and optimizing our cutting-edge infrastructure. Your responsibilities will include:Designing and implementing state-of-the-art GPU compute clustersto support critical workloads. Designing comprehensive automated testing strategies and frameworksacross unit, integration, API, and end-to-end levels for critical commerce flows. Developing robust performance testing frameworksto validate platform scalability, resilience, and identify optimization opportunities. Planning of comprehensive monitoring solutionswith alerting systems to track platform health and ensure SLA compliance. Designing specialized test frameworks for security controlsand ensuring compliance validation across payment and personal data. Architecting a scalable automation infrastructurethat supports growing platform capabilities with consistent test environments. Troubleshooting, diagnosing, and performing root cause analysisof system failures, isolating components and failure scenarios in collaboration with internal and external partners. Optimizing cluster operationsfor maximum reliability, efficiency, and performance.What We Need To See: We are seeking a highly skilled and passionatePlatform Engineerwith: Over 6-8 years of experience working with developing ML Infrastructure. Over 3 years of hands-on experiencein large-scaledirect experience building and deploying production-ready services on Kubernetes. A proven history ofengaging with and contributing to open-source projects . Acollaborative spirit , demonstrated by prior work developing scalable software solutions for cloud services. The ability toeffectively communicate complex technical designs and quality approachesacross various mediums. Adeep understanding of GPU computing and AI infrastructure . A strongpassion for solving complex technical challengesand optimizing system performance. Working knowledge of cluster configuration management toolssuch as BCM or Ansible, and infrastructure-level applications including Kubernetes, Terraform, and MySQL. In-depth understanding of container technologieslike Docker and Containers. Proficiency in programming with Python and Bash scripting.Ways To Stand Out From The Crowd: Candidates who possess the following will be highly competitive: Significant experience with sophisticated infrastructure tooling , including Kubernetes Cluster API, Terraform, Helm, and Operator Framework. Practical, production-level experience across major cloud platforms : Azure, Google Cloud Platform (GCP), or Amazon Web Services (AWS). Ability to adapt to new technologies and Frameworks in ML/GenAI landscape. A strong track record ofsuccessfully refactoring and optimising software for deployment within Kubernetes environments . Comfort discussing and working withcore Kubernetes concepts like CSI, CNI, and CRI . Comprehensive understanding of the CNCF landscapeand its associated tooling. The ability todecompose complex problems into simpler sub-problemsand leverage existing solutions for efficient implementation, along with designing simple, self-sustaining systems. Experience leveragingAI/ML to proactively detect and resolve incidents , automate alert triaging, perform log analysis, and streamline repetitive workflows.