About This Role

This role offers the opportunity to build and scale modern AI platforms that enable next-generation AI, Machine Learning, and Generative AI solutions across the enterprise.</h5><h5>If you are passionate about cloud-native technologies, AI infrastructure, and platform engineering, this is your chance to contribute to a large-scale AI transformation initiative.</h5><h3><strong>Key Responsibilities</strong></h3><ul><li>Support the implementation and enhancement of an enterprise AI Platform running on cloud-native infrastructure using <strong>Red Hat OpenShift</strong> or equivalent Kubernetes platforms.</li><li>Build and integrate AI platform capabilities including <strong>API Gateway, Retrieval-Augmented Generation (RAG) pipelines, AI agent orchestration, model serving, and observability components.</strong></li><li>Deploy, configure, and manage Kubernetes/OpenShift clusters across CPU and GPU environments.</li><li>Automate infrastructure provisioning and platform operations using <strong>Infrastructure-as-Code (IaC), CI/CD pipelines, and DevOps best practices.</strong></li><li>Integrate AI platform services with enterprise infrastructure including networking, storage, load balancers, backup, and security services.</li><li>Implement platform security controls including Identity & Access Management (IAM), Active Directory integration, SIEM, Endpoint Detection & Response (EDR), and Next Generation Firewalls (NGFW).</li><li>Support AI/ML workloads including Large Language Models (LLMs), Generative AI applications, RAG architectures, and agent-based AI frameworks.</li><li>Monitor platform health, optimize performance, manage logging, and support capacity planning to ensure high availability and scalability.</li><li>Collaborate closely with AI engineers, data scientists, DevOps engineers, and enterprise technology teams to deliver secure and reliable AI platform capabilities.</li><li>Continuously evaluate emerging cloud-native and AI platform technologies to improve platform capabilities and operational efficiency.</li></ul><h3><strong>Key Requirements: </strong></h3><ul><li>Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline.</li><li>Minimum <strong>3 years of experience</strong> in Platform Engineering, Cloud Infrastructure, Kubernetes, DevOps, or AI/Data Platform Engineering.</li><li>Hands-on experience with <strong>Kubernetes/OpenShift</strong>, including cluster deployment, networking, operators, and security.</li><li>Experience with Infrastructure-as-Code (Terraform, Ansible, or similar tools).</li><li>Familiarity with CI/CD pipelines and DevOps automation practices.</li><li>Good understanding of enterprise networking, cloud infrastructure, and security principles.</li><li>Exposure to AI platform technologies including:<ul><li>Large Language Models (LLMs)</li><li>Retrieval-Augmented Generation (RAG)</li><li>AI inference/model serving</li><li>Agentic AI frameworks (preferred)</li></ul></li><li>Knowledge of monitoring and observability tools for distributed platforms.</li><li>Strong analytical, troubleshooting, and problem-solving skills.</li><li>Excellent communication and stakeholder collaboration abilities.</li><li>Passion for learning emerging AI and cloud-native technologies.</li></ul><h3><strong>Preferred Qualifications</strong></h3><ul><li>Red Hat OpenShift Certification.</li><li>Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD).</li><li>Experience working with GPU-enabled Kubernetes environments.</li><li>Exposure to MLOps platforms and AI infrastructure.</li><li>Experience supporting enterprise-scale AI or cloud transformation initiatives.</li></ul><h3><strong>Why Join Us</strong></h3><ul><li>Be part of a large-scale AI transformation initiative.</li><li>Work with cutting-edge AI, Generative AI, and cloud-native technologies.</li><li>Collaborate with highly skilled engineering and AI teams.</li><li>Opportunity to shape enterprise AI platforms that power next-generation business capabilities.</li><li>Continuous learning and professional development in one of the fastest-growing technology domains.</li></ul><p>Originally posted on <a href="https://himalayas.app">Himalayas</a></p>

Join an organization at the forefront of AI and Data Analytics transformation, where Artificial Intelligence is being embedded across enterprise platforms to drive innovation, operational excellence, and business value. This role offers the opportunity to build and scale modern AI platforms that enable next-generation AI, Machine Learning, and Generative AI solutions across the enterprise.

If you are passionate about cloud-native technologies, AI infrastructure, and platform engineering, this is your chance to contribute to a large-scale AI transformation initiative.

Key Responsibilities

Support the implementation and enhancement of an enterprise AI Platform running on cloud-native infrastructure using Red Hat OpenShift or equivalent Kubernetes platforms.
Build and integrate AI platform capabilities including API Gateway, Retrieval-Augmented Generation (RAG) pipelines, AI agent orchestration, model serving, and observability components.
Deploy, configure, and manage Kubernetes/OpenShift clusters across CPU and GPU environments.
Automate infrastructure provisioning and platform operations using Infrastructure-as-Code (IaC), CI/CD pipelines, and DevOps best practices.
Integrate AI platform services with enterprise infrastructure including networking, storage, load balancers, backup, and security services.
Implement platform security controls including Identity & Access Management (IAM), Active Directory integration, SIEM, Endpoint Detection & Response (EDR), and Next Generation Firewalls (NGFW).
Support AI/ML workloads including Large Language Models (LLMs), Generative AI applications, RAG architectures, and agent-based AI frameworks.
Monitor platform health, optimize performance, manage logging, and support capacity planning to ensure high availability and scalability.
Collaborate closely with AI engineers, data scientists, DevOps engineers, and enterprise technology teams to deliver secure and reliable AI platform capabilities.
Continuously evaluate emerging cloud-native and AI platform technologies to improve platform capabilities and operational efficiency.

Key Requirements:

Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related discipline.
Minimum 3 years of experience in Platform Engineering, Cloud Infrastructure, Kubernetes, DevOps, or AI/Data Platform Engineering.
Hands-on experience with Kubernetes/OpenShift, including cluster deployment, networking, operators, and security.
Experience with Infrastructure-as-Code (Terraform, Ansible, or similar tools).
Familiarity with CI/CD pipelines and DevOps automation practices.
Good understanding of enterprise networking, cloud infrastructure, and security principles.
Exposure to AI platform technologies including:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- AI inference/model serving
- Agentic AI frameworks (preferred)
Knowledge of monitoring and observability tools for distributed platforms.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent communication and stakeholder collaboration abilities.
Passion for learning emerging AI and cloud-native technologies.

Preferred Qualifications

Red Hat OpenShift Certification.
Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD).
Experience working with GPU-enabled Kubernetes environments.
Exposure to MLOps platforms and AI infrastructure.
Experience supporting enterprise-scale AI or cloud transformation initiatives.

Why Join Us

Be part of a large-scale AI transformation initiative.
Work with cutting-edge AI, Generative AI, and cloud-native technologies.
Collaborate with highly skilled engineering and AI teams.
Opportunity to shape enterprise AI platforms that power next-generation business capabilities.
Continuous learning and professional development in one of the fastest-growing technology domains.

Originally posted on Himalayas