Qureos Mentor

Navikenz

<div><p><b>Job Summary:
</b></p><p>We&rsquo;re looking for an experienced Senior DevOps Engineer who loves working with Kubernetes and AI-driven applications. In this role, you&rsquo;ll be responsible for designing, implementing, and maintaining scalable cloud infrastructure while supporting MLOps pipelines for AI workloads.</p><p><br>
<b>What You&rsquo;ll Be Doing:</b></p>
<div>
<ul><li>Building Scalable Infrastructure: You&rsquo;ll design, implement, and maintain cloud infrastructure using Kubernetes to handle AI and non-AI workloads efficiently.</li></ul>
<ul><li>Developing CI/CD &amp; MLOps Pipelines: Help us automate AI/ML workflows using tools like Kubeflow, MLflow, or Argo Workflows, ensuring seamless deployment and monitoring of AI models.</li></ul>
<ul><li>Optimizing AI Model Deployments: Work with ML engineers to fine-tune LLM models, AI-driven applications, and containerized environments for smooth operation.</li></ul>
<ul><li>Monitoring &amp; Performance Tuning: Keep an eye on Kubernetes clusters and AI workloads, using tools like Prometheus, Grafana, and Loki to ensure high availability and performance.</li></ul>
<ul><li>Automating Everything: Whether it&rsquo;s infrastructure provisioning (Terraform, Helm) or Kubernetes security best practices, you&rsquo;ll help enforce efficiency and compliance.</li></ul>
</div>
<p><b>Staying Ahead of the Curve:</b> You&rsquo;ll have the opportunity to explore and implement emerging AI infrastructure trends, including KServe, Ray, and Triton Inference Server.</p>
<p><b>
What We&rsquo;re Looking For:</b></p>
<div>
<ul><li>8+ years of experience in DevOps, SRE, or Platform Engineering role, with expertise in Kubernetes and cloud-native DevOps</li></ul>
<ul><li>Strong knowledge of Kubernetes fundamentals (deployments, services, ingress, storage, GPU scheduling, multi-cluster management).</li></ul>
<ul><li>Proficiency in scripting &amp; automation with Python, Bash, or Go, particularly for AI-related workflows.</li></ul>
<ul><li>Hands-on experience with AWS, Azure, or GCP, especially in Kubernetes-based AI/ML infrastructure (e.g., Amazon SageMaker, GKE with AI, Azure ML).</li></ul>
<ul><li>Hands-on experience with model deployment frameworks (NVIDIA Triton, vLLM. TGI etc.)</li></ul>
<ul><li>Experience with Distributed computing, multi-GPU training on kubernetes and on-prem GPU clusters.</li></ul>
<ul><li>Experience managing resource allocation and autoscaling for large training/inference workloads. (KEDA, HPA etc.)</li></ul>
<ul><li>Experience with CI/CD &amp; MLOps tools such as Jenkins, Argo CD, Kubeflow, MLflow, or Tekton.</li></ul>
<ul><li>Familiarity with GenAI model deployment, including fine-tuning, inference optimization, and A/B testing.</li></ul>
<ul><li>Hands-on experience with managed ML services (AWS bedrock, Vertext AI models etc.)</li></ul>
<ul><li>Strong problem-solving skills and a mindset of automating repetitive tasks.</li></ul>
<ul><li>Excellent communication skills to collaborate with ML engineers, data scientists, and software teams.</li></ul>
</div>
<p><b>Bonus Points If You Have:</b></p>
<div>
<ul><li>Experience with LLMOps (Large Language Model Operations) and deploying LLM-based applications at scale.</li></ul>
<ul><li>Knowledge of Vector Databases (FAISS, Weaviate, Qdrant) for AI-driven applications.</li></ul></div></div>

Senior DevOps Engineer (Kubernetes & AI Infra)

Join Navikenz and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Navikenz

ABOUT_COMPANY

Senior DevOps Engineer (Kubernetes & AI Infra)