Principal AI Engineering Architect
Tasks
- Architect and ship production multi agent agentic AI systems
- Architect cloud native scalable solutions with AWS first
- Build scalable ML platforms and infrastructure
- Define architectural standards and responsible AI best practices
- Define infrastructure as code and CI CD standards
- Define technical strategy and architecture across cloud data and AI ML
- Design AI ML systems including model serving and MLOps pipelines
- Design and build Amazon Bedrock AgentCore and AWS GenAI solutions
- Design data architectures for batch and streaming
- Drive performance scalability cost and reliability optimization
- Ensure security governance and compliance requirements
- Evaluate emerging technologies and recommend architectural improvements
- Lead cloud migrations and platform modernization
- Lead design reviews and technical discussions
- Maintain architecture documentation standards and guidelines
- Mentor engineers through coaching and code reviews
- Serve as principal technical voice for strategy and direction
Perks/Benefits
- N/A
Skills/Tech-stack
API Design | AWS Bedrock | AWS Bedrock AgentCore | AWS GenAI | AWS Lambda | Airflow | Amazon Bedrock | Amazon Redshift | Apache Kafka | Apache Spark | Autogen | Bedrock AgentCore | BigQuery | CI/CD | Caching | CloudFormation | CrewAI | DBT | Docker | EventBridge | GitHub Actions | Hugging Face | Infrastructure as Code | Injection defenses | Kubernetes | Langchain | Langgraph | MLOps | MLflow | Model Serving | Model routing | MongoDB | Observability | PII handling | PostgreSQL | Prefect | Prompt injection | Prompt injection defenses | PyTorch | Python | Quantization | RAG | SageMaker | Security Governance | Snowflake | TensorFlow | Terraform | Token Economics | Vector Databases | Vertex AI | “as-code”
Education
N/A
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