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Senior Platform Engineer - Distributed Systems

Senior Platform Engineer - Distributed Systems

Grizmo Labs Private LimitedBangalore
1 day ago
Job description

Description :

We're looking for a Senior Platform Engineer to architect and build the robust infrastructure that powers our next-generation Voice AI platform. In this role, you'll design and implement systems that handle massive scale, ensure ultra-low latency, and deliver exceptional reliability. This is a high-impact role where your work will form the technical backbone of real-time AI conversations used by some of India's leading :

  • End-to-end ownership : Drive product development from requirements gathering to architecture, implementation, deployment, and post-launch support.
  • Scale massively : Design and build infrastructure capable of supporting hundreds of thousands of concurrent AI conversations daily.
  • Innovate constantly : Stay on top of the latest research and technology to implement cutting-edge infrastructure solutions.
  • Architect for growth : Design highly scalable, distributed systems that adapt to evolving business needs and product features.
  • Optimise relentlessly : Identify and eliminate system bottlenecks to deliver low-latency, high-throughput performance for real-time voice AI.

Requirements : Core Experience :

  • 5+ years of experience in backend / platform / infrastructure engineering.
  • Proven track record building and scaling distributed systems in production environments.
  • Deep knowledge of Kubernetes (EKS / GKE) - including custom operators, CRDs, and cluster operations.
  • Proficiency in AWS (preferred) or GCP, using Infrastructure-as-Code tools (Terraform, CloudFormation).
  • Strong experience with monitoring and observability stacks (Prometheus, Grafana, ELK).
  • Proficient in Python (especially with FastAPI, asyncio) and / or Go.
  • Systems and Performance :

  • Experience with high-throughput, low-latency systems (ideally in real-time domains).
  • Deep understanding of systems design, caching (Redis), and messaging queues (Kinesis, SQS).
  • Strong expertise with PostgreSQL and Redis.
  • Knowledge of networking, service mesh, and security best practices in cloud environments.
  • Bonus Skills (Nice to Have) :

  • Experience deploying and monitoring machine learning models in production.
  • Familiarity with GPU orchestration (NVIDIA, CUDA) and real-time inference optimization.
  • Knowledge of PyTorch, TensorFlow, or similar ML frameworks.
  • Familiarity with WebRTC, real-time audio processing, or streaming architecture optimisations.
  • Experience with multi-tenant SaaS platforms.
  • (ref : hirist.tech)

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