Information Technology
Full-Time
EPAM Systems
Overview
We are seeking an experienced Cloud AIOps Architect to lead the design and implementation of advanced AI-driven operational systems across multi-cloud and hybrid cloud environments. This role demands a blend of technical expertise, innovation, and leadership to develop scalable solutions for complex IT systems with a focus on automation, machine learning, and operational efficiency.
Responsibilities
Responsibilities
- Architect and design the AIOps solution leveraging AWS, Azure, and Cloud Agnostic services, ensuring portability and scalability
- Develop an end-to-end automated machine learning (ML) pipeline from data ingestion, DataOps, model training, to inference pipelines across multi-cloud environments
- Design hybrid architectures leveraging cloud-native services like Amazon SageMaker, Azure Machine Learning, and Kubernetes for development, model deployment, and orchestration
- Design and implement ChatOps integration, allowing users to interface with the platform through Slack, Microsoft Teams, or similar communication platforms
- Leverage Jupyter Notebooks in AWS SageMaker, Azure Machine Learning Studio, or cloud-agnostic environments to create model prototypes and experiment with datasets
- Lead the design of classification models and other ML models using AWS SageMaker training jobs, Azure ML training jobs, or open-source tools in a Kubernetes container
- Implement automated rule management systems using Python in containers deployed to AWS ECS/EKS, Azure AKS, or Kubernetes for cloud-agnostic solutions
- Architect the integration of ChatOps backend services using Python containers running in AWS ECS/EKS, Azure AKS, or Kubernetes for real-time interactions and updates
- Oversee the continuous deployment and retraining of models based on updated data and feedback loops, ensuring models remain efficient and adaptive
- Design platform-agnostic solutions to ensure that the system can be ported across different cloud environments or run in hybrid clouds (on-premises and cloud)
- 13+ years of overall experience and 7+ years of experience in AIOps, Cloud Architecture, or DevOps roles
- Hands-on experience with AWS services such as SageMaker, S3, Glue, Kinesis, ECS, EKS
- Strong experience with Azure services such as Azure Machine Learning, Blob Storage, Azure Event Hubs, Azure AKS
- Hands-on experience working on the design, development, and deployment of contact centre solutions at scale
- Proficiency in container orchestration (e.g., Kubernetes) and experience with multi-cloud environments
- Experience with machine learning model training, deployment, and data management across cloud-native and cloud-agnostic environments
- Expertise in implementing ChatOps solutions using platforms like Microsoft Teams, Slack, and integrating them with AIOps automation
- Familiarity with data lake architectures, data pipelines, and inference pipelines using event-driven architectures
- Strong programming skills in Python for rule management, automation, and integration with cloud services
- Experience in Kafka, Azure DevOps, and AWS DevOps for CI/CD pipelines
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