Description

You will lead the integration of AI/ML into software development, infrastructure, and reliability workflows.

Responsibilities

• Integrate LLMs into IDEs and CI/CD pipelines for code generation, API scaffolding, and automated testing.
• Build AI agents to detect security flaws, recommend best practices, and ensure compliance with standards like TIISAX, SOC, and FedRAMP.
• Architect AI-enhanced CI/CD pipelines using ArgoCD, Jenkins, or Tekton with predictive deployment and rollback automation.
• Develop AI-driven observability tools to analyze Istio, Prometheus, and logging data for anomaly detection and automated fixes.
• Automate infrastructure management by using AI to refactor Terraform modules and translate code to CloudFormation.
• Partner with engineering, QA, and SRE teams to lead POCs and production rollouts of AI-driven workflows.

Required Skills

• 7+ years of experience in cloud architecture, DevOps, or full-stack engineering.
• 2+ years of experience applying AI/ML specifically within software engineering workflows.
• Deep expertise with AWS, GCP, and Azure cloud environments.
• Proficiency with Terraform, Helm, and Kubernetes.
• Hands-on experience with CI/CD tools including ArgoCD, Jenkins, or Tekton.
• Strong full-stack development skills in Node.js, Python, and React/Vue.
• Experience with observability frameworks such as Prometheus, OpenTelemetry, or ELK.
• Proven track record of building or integrating AI-enhanced developer tools.

Preferred Skills

• Experience with MLOps platforms like MLflow, SageMaker, or Kubeflow.
• AWS/GCP Architect or CKA certifications.

Key Skills

Education

Any Graduate