5 Ai Ops Jobs

Job role & responsibilities:- Collaborate with different teams to propose AI solutions on different use cases across the insurance value chain, with a focus on AIops and MLOps Research, build, and deploy AI models as part of the broader AI team, leveraging AIops and MLOps practices for efficient model management Contribute to our DevOps practices using OpenShift or Azure ML DevOps Technical Skills, Experience & Qualification required:- Expertise is required in the following fields: 6-9 years of progressive experience in AI and ML, with a focus on AIops and MLOps Experience in ML Flow or Cube Flow or Airflow, ML Ops, more in to production deployment Experience in deploying and managing AI models in production environments using Azure ML DevOps or OpenShift Implementation of at least 5 AI projects, preferably with experience in AIops and MLOps Experience with Azure, OpenShift, MLFlow DevOps for model deployment, monitoring, and management Setting up CI/CD pipelines using Azure DevOps, Jenkins, etc. Hands-on experience with Generative AI tech LLMs, RAG, Prompt Engineering Broad understanding of machine learning algorithms and techniques, including LLMs/SLMs, CNNs) RNNs, transformers, and attention mechanisms Immediate Joiners will be preferred

We are seeking a Senior Prisma SD-WAN consukltnt to work with Palo Alto Networks. It is an initial 12 month Freelace Contract highly likely to extend. Mandatory Requirements: Networking Expert with CCIE certification At Least 8 years experience designing and deploying with: Prisma SDWAN design and deployment experience - Mandatory ION device design and hands on deployment experience - Mandatory Integration with Prisma SASE Panorama Log Collectors Strata Cloud Manager AI OPS Design and Architecture skills with Palo Alto and other SDWAN solutions Able to guide an implementation team and drive project conversations with Senior Leadership and Project Stakeholders Excellent customer management skills Preferred Skills: Project management skills Leading large technical engagements with enterprise customers Experience with Prisma Access and CIE Preferred Skills: Project management skills Leading large technical engagements with enterprise customers Experience with Prisma Access and CIE

The ideal candidate has 6-12 years of experience in infrastructure design, optimization, and integration. AI OPs and ITOM skills are a must.

Primary Skill AI Ops Secondary Skills (Good to Have Skills) Moogsoft or Netcool experience, Automation, Self-Healing and scripting Onshore

Azure Cloud Expert (AI Labs)-IC -AM Associate Director-BLR - J48797 Key Responsibilities Cloud Infrastructure Management: Design, deploy, and manage AI solutions on Azure AI Studio and Google Cloud Platform (GCP). Optimize cloud resources to ensure cost-effectiveness and high performance. CI/CD Pipeline Development: Develop and maintain continuous integration and continuous deployment pipelines for AI applications. Automate deployment processes to streamline workflows and reduce time-to-market. Hardware Integration: Manage and configure specialized hardware workstations including HP Fury Z8, Dell 7960 XCTO, and Nvidia GCX Studio A100. Ensure seamless integration between cloud services and on-premises hardware resources. AI/ML Operations: Implement AI Ops, ML Ops, and RAG Ops practices to enhance the reliability and scalability of AI systems. Monitor system performance, troubleshoot issues, and implement improvements. Collaboration and Support: Collaborate with cross-functional teams to understand requirements and deliver robust AI solutions. Provide technical support and guidance to team members regarding DevOps best practices and tools. Security and Compliance: Ensure all deployments adhere to security standards and compliance regulations. Implement and maintain security protocols for both cloud and on-premises environments. Qualifications Education: Bachelors degree in Computer Science, Engineering, or a related field. Masters degree preferred. Experience: Proven experience as a DevOps Engineer, preferably within AI or machine learning environments. Strong expertise in Azure AI Studio and developing AI solutions on the Azure platform. Experience with Google Cloud Platform (GCP) in deploying and managing AI solutions. Technical Skills: Proficiency with cloud services, including compute, storage, networking, and AI/ML tools on Azure and GCP. Hands-on experience with CI/CD tools such as Jenkins, GitLab CI, or Azure DevOps. Familiarity with containerization and orchestration technologies like Docker and Kubernetes. Knowledge of infrastructure as code (IaC) tools such as Terraform or Azure Resource Manager. Experience with specialized hardware workstations: 1HP Fury Z8 2Dell 7960 XCTO 3Nvidia GCX Studio A100 Understanding of AI Ops, ML Ops, and RAG Ops methodologies. Soft Skills: Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities. Ability to manage multiple tasks and prioritize effectively in a fast-paced environment. Preferred Qualifications Certifications in Azure (e.g., Azure DevOps Engineer Expert) or Google Cloud (e.g., Professional DevOps Engineer). Experience with monitoring and logging tools such as Prometheus, Grafana, or Azure Monitor. Knowledge of scripting languages like Python, Bash, or PowerShell. Familiarity with version control systems, particularly Git. Required Candidate profile Candidate Experience Should Be : 8 To 14 Candidate Degree Should Be : BE-Comp/IT,BE-Other,BTech-Comp/IT,BTech-Other,MBA,MCA