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Senior Software Engineer - Google Kubernetes Engine
Senior Software Engineer - Google Kubernetes EngineGrizmo Labs Private Limited • Bangalore
Senior Software Engineer - Google Kubernetes Engine

Senior Software Engineer - Google Kubernetes Engine

Grizmo Labs Private Limited • Bangalore
30+ days ago
Job description

Description :

We're looking for a Senior Software Engineer who can architect and build robust infrastructure systems that power our voice AI platform. You'll be the backbone of our technology, ensuring our systems can handle massive scale while maintaining high performance and :

  • Own end-to-end product development - from requirement gathering and architecture design to implementation and launch, you'll shepherd features through their complete lifecycle.
  • Build for massive scale - develop systems that can handle hundreds of thousands of calls per day with high reliability and performance.
  • Innovate through research - stay current with cutting-edge technologies, read research papers, and implement state-of-the-art solutions that give us a competitive edge.
  • Architect distributed systems - design robust, scalable infrastructure that can handle our growing customer base and evolving product requirements.
  • Optimize for performance - identify and resolve bottlenecks to ensure our voice AI delivers natural, real-time conversations without latency issues.

Requirements :

  • 5+ years in backend / platform / infrastructure engineering with distributed systems experience.
  • Deep hands-on experience with Kubernetes (EKS, GKE), including operators, custom resources, and cluster management.
  • Proficiency in cloud platforms (AWS preferred, GCP) with infrastructure-as-code (Terraform, CloudFormation).
  • Expertise in monitoring and observability (Prometheus, Grafana, ELK stack).
  • Solid programming skills in Python (FastAPI, asyncio), Go, or similar systems languages.
  • Systems and Performance :

  • Experience building high-throughput, low-latency systems (preferably real-time applications).
  • Strong grasp of systems design, caching strategies (Redis), and message queues (Kinesis, SQS).
  • Database expertise (PostgreSQL, Redis).
  • Understanding of networking, service mesh, and security best practices.
  • Bonus : MLOps and AI Infrastructure :

  • Experience with ML model deployment, versioning, and monitoring in production.
  • Background in GPU orchestration for AI workloads (NVIDIA GPUs, CUDA optimization).
  • Knowledge of real-time audio processing, WebRTC, or voice / video streaming systems.
  • Experience with ML frameworks (PyTorch, TensorFlow) and inference optimization.
  • Previous work on multi-tenant or single-tenant SaaS platforms.
  • Startup Mindset :

  • You've built, broken, and fixed systems in production at scale.
  • Comfortable with a fast-paced environment where you'll own critical infrastructure decisions.
  • Collaborative approach - you work well with AI teams, product, and founders.
  • Growth-minded and excited about scaling infrastructure for rapid business growth.
  • (ref : hirist.tech)

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