Cloud & Platform Engineer

Qualitykiosk Technologies; United States; Remote; USD 100,000 - 160,000; Full time

Job summary

A leading technology firm is searching for a Cloud & Platform Engineer specializing in AI deployments. You will play a crucial role in building cloud-native infrastructure and integrating advanced AI functionalities into enterprise systems. Successful candidates should have solid experience in GCP, Kubernetes, and Docker, combined with a passion for innovative technology solutions.

Benefits

Fast-paced execution

Ownership from day one

Cross-functional collaboration

Qualifications

• 3–6 years in cloud infrastructure engineering or DevOps.
• Proven experience with GCP, Kubernetes, and Docker.
• Familiarity with modern LLM stacks.

Responsibilities

• Design and deploy microservice-based architecture.
• Build and manage CI/CD pipelines.
• Integrate external APIs securely.

Skills

Cloud infrastructure engineering

DevOps

Google Cloud Platform (GCP)

Kubernetes

Docker

OAuth2

GitOps-style CI/CD

Job description

Job Title:

Cloud & Platform Engineer AI Agent & Platform Deployment (GCP Preferred)

Location:

Remote / Hybrid (India preferred)

About the Role:

We are building an enterprise-ready AI agent and AI framework. This role is central to the success of the platform — you'll lead the design, deployment, and scaling of cloud-native infrastructure, enabling smooth operation of the agent across GCP and other cloud providers.

You’ll work closely with AI engineers, product managers, and QA leaders to operationalize an LLM-based stack integrated with enterprise tools like Jira, Zephyr, and Selenium.

Key Responsibilities:

• Design and deploy secure microservice-based architecture (Docker, Kubernetes, API Gateway)
• Build and manage CI/CD pipelines across cloud environments (GCP, AWS, Azure)
• Orchestrate cloud-native LLM endpoints (e.g., OpenAI, Claude, PaLM)
• Integrate external APIs securely (OAuth2 flows with Jira, TestRail, etc.)
• Manage vector DBs (Pinecone, FAISS, or Weaviate) and inference caching (Redis/in-memory)
• Set up observability: logging, alerting, audit trails (Cloud Logging, Prometheus, etc.)
• Implement TLS, JWT auth, secret management (Vault, Secret Manager)
• Optimize cost and scalability across multi-agent workflows

Required Skills:

• 3–6 years in cloud infrastructure engineering or DevOps
• Proven experience with:
• Google Cloud Platform (GCP)
• Kubernetes & Docker
• API gateways (NGINX/Istio/Kong)
• Familiarity with modern LLM stacks (LangChain, Haystack, OpenAI APIs)
• Strong understanding of OAuth2, JWT, HTTPS/TLS, role-based access
• GitOps-style CI/CD (Cloud Build, GitHub Actions, ArgoCD)

Nice to Have:

• Knowledge of LLMOps or MLOps principles
• Prior experience with test automation tools (Selenium, Playwright)
• Background in working with QA or developer productivity tools
• Contributions to open-source infra tools or AI orchestration frameworks

Why Join Us?

• Be a founding infra engineer on an enterprise AI platform
• Work on the intersection of cloud, AI agents, and enterprise automation
• Fast-paced execution, ownership from day one, and cross-functional collaboration