DevOps Engineer SE II - GCP & 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)

Requirements

Requirements

• 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

- 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