Cloud Engineer

• Design and implement AI-driven developer workflows that optimize coding, testing, deployment, and debugging.
• Build intelligent agents to recommend best practices, detect security risks, and ensure compliance with standards such as SOC, FedRAMP, and AWS GovCloud.
• Integrate advanced language models (e.g., GPT, Claude, CodeLlama) into developer tools and CI/CD pipelines.
• Define integration strategies and APIs that enable shared AI components and models across teams or business units.
• Fine-tune large language models to align with internal codebases, architectures, and operational requirements.
• Design scalable CI/CD pipelines supporting multi-cloud and on-premise environments using platforms such as ArgoCD, Jenkins, or Tekton.
• Embed AI into deployment workflows for predictive analysis, rollback automation, and zero-downtime release strategies.
• Enhance observability with AI-driven log summarization, anomaly detection, event correlation, and proactive alerting.
• Develop self-healing infrastructure that reduces operational overhead and accelerates developer productivity.
• Automate vulnerability detection, prioritization, and remediation using AI-based scanners and classifiers.
• Use AI and NLP to improve infrastructure-as-code quality and generate automated fixes for configuration issues.
• Convert compliance documentation into policy-as-code frameworks to streamline governance and auditing.
• Collaborate with security and infrastructure teams to strengthen platform resilience and reduce incident response times.
• Partner across engineering, QA, SRE, and documentation teams to align AI initiatives with broader technical goals.
• Lead proof-of-concept efforts and performance benchmarks to validate and scale AI-driven workflows.
• Promote AI/ML adoption through mentorship, training, and architectural guidance.
• Coordinate with other teams or units to share, evaluate, or co-develop AI tools, APIs, and model capabilities.
• Leverage AI to automate test case generation for APIs, microservices, and infrastructure.
• Use AI tools to generate test data, assess coverage, and recommend testing improvements.
• Implement AI-based load testing pattern generation and automated analysis of test results.

Software Development Cloud Architect

Cloud Engineer

Cloud Engineer – AWS