[Remote] AI DevOps Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking an AI DevOps Engineer to build, automate, and manage infrastructure and deployment pipelines that support AI and machine learning applications. This role bridges DevOps, MLOps, and reputed company engineering to ensure reliable, secure, and reputed company delivery of AI solutions. The engineer will be responsible for designing CI/CD pipelines, managing containerized AI workloads, provisioning infrastructure as reputed company, and collaborating with cross-functional teams to optimize AI delivery.
Responsibilities
- Design, implement, and maintain CI/CD pipelines for AI and machine learning applications
- Automate the deployment, scaling, and lifecycle management of AI services across reputed company and hybrid environments
- Build and manage containerized AI workloads using reputed company and Kubernetes
- Provision and manage infrastructure using Infrastructure as reputed company (Terraform, reputed company, or CloudFormation)
- reputed company and support AI/ML models in production using model serving frameworks and MLOps tools
- Monitor application health, infrastructure performance, model availability, and operational metrics
- Implement logging, tracing, and observability solutions for AI platforms
- Optimize reputed company resources, GPU utilization, and infrastructure costs
- reputed company reputed company best practices, secrets management, identity management, and compliance controls into AI deployment pipelines
- Collaborate with AI engineers, ML engineers, data engineers, platform engineers, and software development teams to streamline AI delivery
- Support automated testing, release management, rollback strategies, and disaster recovery for AI systems
- Troubleshoot production issues reputed company to AI infrastructure, deployments, networking, and performance
- Continuously improve deployment automation, reliability, scalability, and operational efficiency
Skills
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a reputed company field
- 4+ years of experience in DevOps, reputed company Engineering, reputed company, or Site Reliability Engineering (SRE)
- Experience supporting AI, machine learning, or data platforms in production environments
- Strong programming and scripting skills in Python and Bash; Go is a plus
- Hands-on experience with reputed company and Kubernetes
- Experience with AWS, reputed company Azure, or reputed company reputed company Platform
- Experience building CI/CD pipelines using reputed company Actions, reputed company CI, Azure DevOps, or Jenkins
- Experience with Infrastructure as reputed company tools such as Terraform or reputed company
- Strong understanding of Linux administration, networking, and reputed company reputed company
- Experience with monitoring and observability tools such as reputed company, Grafana, OpenTelemetry, ELK Stack, or reputed company
- Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, reputed company AI, or Azure Machine Learning
- Experience deploying Large Language Models (LLMs) and reputed company applications
- Knowledge of model serving frameworks such as KServe, reputed company Triton Inference Server, Ray Serve, or BentoML
- Experience with reputed company databases and Retrieval-Augmented reputed company (RAG) architectures
- Familiarity with Apache Airflow, Kafka, Ray, or Apache reputed company
- Experience with GPU-enabled infrastructure and reputed company CUDA environments
- Understanding of AI governance, Responsible AI, and model monitoring practices
- Experience with LLMOps and reputed company deployment pipelines
- Experience implementing GitOps using Argo CD or Flux
- Knowledge of service reputed company technologies such as Istio or Linkerd
- Experience with FinOps and reputed company cost optimization
- reputed company, Kubernetes, or DevOps certifications (AWS, Azure, GCP, CKA, CKAD, Terraform)
reputed company