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About Us: Waltcorp is at the forefront of cloud engineering, helping businesses transform their operations by leveraging the power of AWS. We are seeking a skilled and visionary AWS DevOps Solutions Architect - ML/AI Focus to design and implement cloud solutions that address our clients' complex business challenges.Key Responsibilities: Solution Design:Collaborate with stakeholders to understand business requirements and design scalable, secure, and high-performing AWS cloud architectures. Technical Leadership:Serve as a technical advisor, guiding teams on AWS best practices, services, and tools to optimize performance, security, and cost efficiency. Infrastructure Development:Architect and oversee the deployment of cloud solutions using AWS services such as EC2, S3, Lambda, RDS, and more. Infrastructure as Code (IaC) & Cloud Automation: Design, implement, and manage infrastructure usingTerraform ,AWS CloudFormation , orCDK . Automate provisioning of compute, storage, and networking resources using AWS services likeEC2, S3, VPC, IAM, EKS, ECS . c) Implement and maintainCI/CD pipelines(usingCodePipeline ,Jenkins ,GitHub Actions , orGitLab CI ). ML Model Deployment & Automation (MLOps) Build and optimizeend-to-end ML pipelinesusingSageMaker Pipelines ,Kubeflow , orMLflow . Automate training, testing, validation, and deployment of ML models in staging and production environments. Support model versioning, reproducibility, and lineage tracking using tools likeDVC ,SageMaker Model Registry , orMLflow . Monitoring & Logging Implement monitoring for both infrastructure and ML workflows usingCloudWatch ,Prometheus ,Grafana ,SageMaker Model Monitor . Set up alerting for anomalies in ML model performance (data drift, concept drift). Ensure application logs, model outputs, and system metrics are centralized and accessible. Containerization & Orchestration Containerize ML workloads usingDockerand orchestrate usingEKS (Kubernetes)orECS . Optimize resource usage through autoscaling and right-sizing of ML workloads in containers. Data & Experiment Management Integrate withdata versioning tools(e.g., DVC or LakeFS) to track datasets used in model training. Enable experiment tracking usingMLflow ,Weights & Biases , orSageMaker Experiments . Support reproducible research and automated experimentation pipelines. Client Engagement:Communicate complex technical solutions to non-technical stakeholders and deliver high-level architectural designs, presentations, and proposals. Integration and Migration:Plan and execute cloud migration strategies, integrating existing on-premises systems with AWS cloud infrastructure. Security and Compliance:Implement robust security measures, including IAM policies, encryption, and monitoring, to ensure compliance with industry standards and regulations. Documentation:Develop and maintain detailed technical documentation for architecture designs, deployment processes, and configurations. Continuous Improvement:Stay current with AWS advancements and emerging trends, recommending updates to architecture strategies and tools.Qualifications: Educational Background:Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience). Experience:5+ years of experience in cloud architecture, with a focus on AWS. Technical Expertise: Strong knowledge of AWS core services, including compute, storage, networking, and database solutions. Proficiency in Infrastructure as Code (IaC) tools like Terraform, AWS CloudFormation, or AWS CDK. Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, ECS, or EKS). Understanding of DevOps practices, CI/CD pipelines, and automation. Strong command of networking concepts such as VPCs, load balancing, and security groups. Familiarity with scripting languages like Python or Bash. Soft Skills: Excellent communication, presentation, and interpersonal skills. Ability to translate business needs into technical solutions. Strong analytical and problem-solving abilities. Preferred Qualifications: AWS Certified Solutions Architect (Associate or Professional) and AWS DevOps certifications. Expertise in engineering and maintaining MLOps and AI applications Experience in hybrid cloud or multi-cloud environments. Familiarity with monitoring and logging tools such as CloudWatch, ELK Stack, or Datadog.Why Join Us? Competitive compensation and benefits. Opportunity to work on transformative projects with industry-leading clients. Access to continuous learning and certification programs. A collaborative, innovative, and inclusive work culture.  How to Apply: If you’re passionate about architecting cutting-edge cloud solutions, we’d love to hear from you. Be a part of a team shaping the future of cloud technology!Skills Amazon Web Services (AWS) Continuous Integration and Continuous Delivery (CI/CD) Amazon CloudWatch Elastic Stack (ELK) ECS ECR Datadog Infrastructure as code (IaC) Kubernetes Docker Linux AWS CLI DevOps