AI Engineer (Expert)

Requirements

• System Architecture Design: Proven experience in designing and building agentic system architectures using
  
• frameworks like Amazon Bedrock AgentCore.
  
• Multi -Step Reasoning: Strong expertise in orchestrating multi -step reasoning, tool invocation, and workflow
  
• automation for AI agents.
  
• Model Training and Deployment: Deep hands -on knowledge of training and deploying models using PyTorch
  
• and TensorFlow.
  
• Containerization: Skills in Docker and Kubernetes for scalable and fault -tolerant ML/GenAI deployments.
  
• Networking for ML Workloads: Solid understanding of networking principles, including VPC design and lowlatency
  
• communication patterns.
  
• MLOps Practices: Experience with CI/CD for models, model versioning, and observability in ML systems.
  

• Cloud Services Experience: Prior experience with Amazon Bedrock and other cloud -managed foundation model
  
• services.
  
• Infrastructure as Code: Familiarity with tools like Terraform for reproducible cloud infrastructure.
  
• Serverless Architecture: Knowledge of serverless components (e.g., AWS Lambda) for event -driven workflows.
  
• Data Engineering: Experience in building reliable ETL/data pipelines for model training and feature stores.
  
• Observability Tools: Familiarity with observability stacks like Prometheus and Grafana for monitoring ML
  
• services.
  
• Enterprise Compliance: Understanding of compliance considerations in regulated industries (e.g., automotive,
  
• finance).