Hiring Now: Kubernetes Engineer – Turium AI | Hyderabad (On-Site, Full-Time)

Job Description
Turium AI is redefining enterprise operations through advanced, secure AI systems. With a mission to power intelligent transformation, we build scalable and resilient AI infrastructure solutions for global enterprises. Join a dynamic team driving innovation at the intersection of AI and cloud-native technology.
Requirements
They are seeking a Kubernetes Engineer to design and maintain scalable Kubernetes-based infrastructure powering our AI and ML platforms. You will collaborate with cross-functional teams to support end-to-end AI workload deployment, monitoring, and optimization on modern cloud platforms.
Key Responsibilities
- Design, deploy, and manage Kubernetes clusters (EKS, GKE, AKS)
- Develop and manage Helm charts, manifests, and Kubernetes controllers
- Build CI/CD automation using GitHub Actions, ArgoCD, or Jenkins
- Implement observability with Prometheus, Grafana, ELK/EFK, or Loki
- Enable GPU scheduling, model deployments, and ML pipeline scaling
- Enforce security best practices (RBAC, secrets, network policies)
- Troubleshoot staging and production deployment issues
- Work closely with DevOps, ML engineers, and security teams
Required Qualifications
- 3–6 years in DevOps, SRE, or Platform Engineering
- Production experience with Kubernetes and Helm
- Proficiency with IaC tools like Terraform or Pulumi
- Familiar with AWS, Azure, or GCP cloud platforms
- Strong scripting skills in Bash, Python, or Go
- Understanding of service mesh (Istio) and container networking
- Knowledge of container security best practices
Preferred Qualifications
- Experience with GPU workloads, Kubeflow, MLflow, or AI/ML pipelines
- CNCF Certifications (CKA, CKAD)
- Familiarity with eBPF, serverless tools, or service mesh tuning
- Availability to work in AEDT/AEST time zones
What We Offer
- Competitive salary with performance-based bonuses
- Work with cutting-edge AI/ML infrastructure
- Collaborate with global experts in DevOps and MLOps
- Exposure to enterprise AI, Kubernetes, DevSecOps, and observability
- Flexible hours and a remote-friendly culture
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