DevOps Engineer (AWS / Kubernetes / Agentic AI)

ZentixSoft is looking for a DevOps Engineer! 🚀

Format: Full-Time Outstaffing, long-term remote project. You will take ownership of production AWS and Kubernetes infrastructure while building and integrating Agentic AI workflows into CI/CD, monitoring, and developer platforms.

💡 Why ZentixSoft?
💸 Salary Review: A structured system of compensation reviews aligned with your engineering growth.
⚖️ Work-Life Balance: Sustainable workflows with no senseless overtime, helping you keep your resource fully charged.
🦾 Trust and Transparency: Zero micromanagement and no invasive time-trackers—we fully trust your professional autonomy.
🎁 Gifts & Culture: Corporate gifts for holidays, birthdays, and a true team atmosphere where your voice always matters.

🧩 Responsibilities:
Cloud & Platform Operations: Build, maintain, and evolve production AWS infrastructure (EKS, EC2, RDS/Aurora, ElastiCache, S3, IAM, VPC, Route 53, ALB/NLB, ECR).
GitOps & Kubernetes Workloads: Manage Kubernetes environments using Helm, Argo CD, External Secrets Operator (ESO), and GitOps best practices.
Infrastructure as Code & CI/CD: Architect Terraform modules and maintain robust GitHub Actions pipelines (including automated PR preview environments).
Agentic AI & Engineering Automation: Build and integrate tool-using AI agents, MCP integrations, and LLM-powered workflows to automate infrastructure, incident response, and CI/CD operations.
Observability & Compliance: Implement SOC2-compliant monitoring, alerting, and telemetry while troubleshooting production networking, database, and deployment incidents.

🎓 Requirements:
DevOps Background: 3+ years of hands-on DevOps, Platform, or SRE experience with production systems.
AWS & Kubernetes Expertise: Strong experience with AWS ecosystems and Amazon EKS cluster management.
GitOps & IaC Stack: Practical experience with Argo CD, Helm, Terraform, and GitHub Actions.
Agentic AI Ecosystem: Practical experience or strong ability to build tool-using AI agents, LLM-powered automation, function calling, and frameworks (e.g., LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, or MCP).
Core Systems Knowledge: Solid understanding of Linux, networking, DNS, TLS, IAM, and container runtime internals.
US Schedule Alignment: Ability to work with substantial overlap during US business hours (9am – 5pm ET).

📍 Project Details:
⏳ Duration: Long-term (Full-time contract).
🕒 Timezone: 9am – 5pm ET overlap.
📍 Location: Fully Remote.