Platform Engineer – AI Infrastructure

AI Platform Infrastructure

• Design, implement, and manage AWS cloud infrastructure supporting Shadowlab AI applications and services.
• Ensure scalability, reliability, and security of the AI platform architecture.
• Configure and manage compute, storage, networking, and access management components within AWS.
• Implement infrastructure provisioning using Infrastructure-as-Code (IaC).

DevOps and CI/CD Enablement

• Design and maintain CI/CD pipelines for AI applications and internal tools.
• Automate build, testing, and deployment processes across development, staging, and production environments.
• Integrate version control repositories with deployment pipelines.
• Implement deployment standards and release management processes for the AI platform.

Platform Operations and Reliability

• Monitor system performance, availability, and security across the AI platform.
• Implement logging, monitoring, and alerting mechanisms for infrastructure and services.
• Troubleshoot and resolve issues related to infrastructure, deployments, and system integrations.
• Ensure compliance with IT security and governance standards

Data and AI System Enablement

• Support infrastructure for AI workloads, data pipelines, and integration services.
• Enable secure connectivity between internal systems, databases, APIs, and AI services.
• Optimize infrastructure performance for AI-driven applications, chatbot services, and automation workflows.

Development Support and Engineering

• Assist development teams in deploying and scaling AI applications and backend services.
• Contribute to development of platform utilities, automation scripts, and system integrations.
• Participate in system architecture design, technical reviews, and performance optimization

Documentation and Continuous Improvement

• Document platform architecture, infrastructure configurations, and deployment standards.
• Recommend improvements to development workflows, platform reliability, and system performance.
• Promote DevOps best practices across the Application Development and Shadowlab teams.