DevOps / Cloud Engineer with Agentic AI (AgentOps / LLMOps)

Job Description: DevOps / Cloud Engineer with Agentic AI (AgentOps / LLMOps)

Company: Vorizo Infotech
Role: DevOps / Cloud Engineer (Agentic AI), open to Senior, Lead and Architect levels
Experience: 5 to 15 years

How to apply Email: [email removed] WhatsApp: [phone removed] Subject: DevOps / Cloud Engineer (Agentic AI) | 515 Years

About the role
We are looking for a DevOps or Cloud professional who can build and run the infrastructure behind AI agents. You will set up secure, scalable platforms where agentic AI applications are deployed, monitored, evaluated and improved, and you will use AI agents to automate DevOps work as well.

Key Result Areas (KRA)

1. Cloud and platform engineering: design and manage scalable, secure cloud infrastructure for AI and agent workloads.
2. CI/CD and automation: build pipelines to test, deploy and release agentic AI applications and models quickly and safely.
3. AgentOps and LLMOps: set up monitoring, tracing, evaluation and versioning for prompts, models and agents.
4. AI-driven operations: build agents that automate incident response, log analysis, deployments and infrastructure tasks, with human approval.
5. Security and governance: apply guardrails, access control, secrets management, data privacy and compliance to AI systems.
6. Reliability and cost: keep AI services available and fast, and control GPU, token and cloud spend.

Key Performance Areas (KPA)

• Deployment frequency, release success rate and lead time
• System uptime, latency and incident resolution time
• Agent reliability, task success rate and evaluation scores
• Cloud and LLM cost against budget
• Security findings closed and compliance adherence
• Quality of automation, runbooks and documentation
• Reusability of pipelines and infrastructure templates
• Collaboration with development, data and security teams

Mandatory skills

• 5+ years in DevOps or cloud engineering on AWS, Azure or GCP
• Docker and Kubernetes, with Infrastructure as Code (Terraform or similar)
• CI/CD tools (Jenkins, GitHub Actions, GitLab CI or Azure DevOps) and Git
• Monitoring and observability (Prometheus, Grafana, ELK or similar)
• Working knowledge of LLM and agentic AI applications, including deploying and operating them
• Scripting in Python, Bash or similar, and REST APIs
• Security basics: IAM, secrets management and network security

Good to have

• LLMOps and AgentOps tools for tracing and evaluation (LangSmith, Langfuse, MLflow or similar)
• Agent frameworks (LangChain, LangGraph, CrewAI, AutoGen) and the Model Context Protocol (MCP)
• Cloud AI services (AWS Bedrock, Azure OpenAI, Google Vertex AI)
• Vector databases, GPU workloads and model serving
• Cloud or Kubernetes certifications

How to apply
Email: [email removed]
WhatsApp: [phone removed]
Subject: DevOps / Cloud Engineer (Agentic AI) | 5–15 Years