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Keywords Studios

DevOps Engineer SE II - GCP & AI

Reposted 10 Days Ago
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In-Office
Pune, Mahārāshtra, IND
Senior level
In-Office
Pune, Mahārāshtra, IND
Senior level
The DevOps Engineer will manage GCP infrastructure, build AI deployment pipelines, implement security measures, and optimize costs while ensuring system observability.
The summary above was generated by AI
Responsibilities:
  • Infrastructure Ownership: Own Helpshift production services and ensure complete monitoring coverage, troubleshoot and fix production issues.
  • Infrastructure as Code (IaC): Design and maintain scalable GCP infrastructure using Terraform o
  • AI Orchestration & LLMOps: Build deployment pipelines for AI agents, managing vector databases (e.g., Vertex AI Search, Pinecone, Weaviate, ElasticSearch) and model endpoints.
  • Security (DevSecOps): Implement "Security-by-Design," including IAM least-privilege access, secret management (Secret Manager), and automated vulnerability scanning for AI workloads.
  • CI/CD Excellence: Architect high-velocity pipelines for both traditional microservices and AI model prompts/configurations. Design, implement, and maintain secure CI/CD pipelines for automating deployment, configuration, and testing processes.
  • Observability: Set up comprehensive monitoring for system health and LLM-specific metrics (latency, token usage, and cost)
  • Cloud Governance: Optimise GCP costs and manage resource quotas, especially for GPU/TPU-intensive AI tasks.
  • Cross Cloud Deployment: Establish & Optimise the connectivity among apps deployed in different cloud environments (AWS <> GCP)

RequirementsRequirements
  • Relevant experience of 6+ years and above
  • Expert-level Google Cloud Platform (GCP) administration skills: GKE, Cloud Run, Vertex AI, GCS, NEG etc
  • Experience deploying Vector Databases (Pinecone, Weaviate, ElasticSearch or Vertex Search) and managing API rate limits/throttling for LLM providers.
  • Setting up Cloud Monitoring/Logging specifically for AI metrics: token consumption, inference latency, and model error rates.
  • In-depth knowledge of running/managing UNIX-like operating systems (we use Ubuntu)
  • Strong knowledge of networking protocols, security architectures, and identity and access management (IAM) principles.
  • Experience with containerisation technologies (e.g., Docker, Kubernetes) and securing containerised environments.
  • Proficiency in Python and Bash
  • Experience in designing and building solutions that are highly scalable, fault tolerant and cost-effective
  • Experience with IaaC tools like Ansible, Terraform.
  • Ability to analyse bottlenecks in architecture and quickly debug to reach a resolution for issues
  • Have an automation mindset and ability to reason and work with complex systems.
  • Excellent communication and documentation skills
  • Quick learner and good mentor for junior team members

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