Data Scientist - AgenticAI

Tasks

• Analyze performance and optimize cost
• Architect Agentic AI solutions
• Automate infrastructure provisioning
• Build agentic workflows
• Build microservices
• Build proof of concept genai
• Collaborate with security analysts
• Create CI/CD pipelines for ML
• Deploy and maintain AI systems
• Design multi-agent systems
• Develop REST APIs
• Implement MLOps best practices
• Integrate agentic AI into security workflows
• Manage model versioning
• Monitor models and infrastructure
• Operationalize Large Language Models
• Own machine learning lifecycle
• Set up automated testing and rollback

Perks/Benefits

• Equal employment opportunity
• Health insurance
• Life insurance
• Personal accident insurance

Skills/Tech-stack

AWS Bedrock | AWS CodePipeline | AWS Lambda | Amazon ECS | Amazon EKS | Amazon SageMaker | Anomaly Detection | Automated retraining | CI/CD | CloudWatch | CrewAI | DVC | Data Pipelines | Docker | Embeddings | Feature Engineering | GitHub Actions | Grafana | Infrastructure as Code | Jenkins | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | MLflow | Machine Learning | Microservices | Model Evaluation | Model Monitoring | Prometheus | Prompt engineering | Python | RAG | REST APIs | Retrieval-Augmented Generation | S3 | Series analysis | Terraform | Time Series | Time Series Analysis | Vector Database | “as-code”