Senior AI Engineer
Tasks
- Build AI agent skills and orchestration patterns
- Build and deploy secure scalable AI solutions
- Develop evals and red teaming protocols
- Develop governed datasets feature pipelines and model inference
- Drive CI/CD and deployment standards for AI systems
- Ensure auditable explainable and compliant AI outputs
- Implement RAG and knowledge base workflows
- Implement monitoring and observability for model lifecycle
- Implement prompt injection defenses and content filtering
- Manage data lineage and model versioning
- Mentor engineers and conduct code reviews
- Optimize cost and performance for AI workloads
- Perform incident response for AI platform issues
- Ship production LLM pipelines and APIs
- Support architecture reviews and ADRs
Perks/Benefits
- N/A
Skills/Tech-stack
AWS AgentCore | AWS AgentCore Gateway | AWS AgentCore Harness | AWS ECS | AWS Serverless | AWS Serverless Application Model | Access Control | Agent Orchestration | AgentCore Gateway | Application Model | CI/CD | Content Filtering | Data Lineage | Databricks | Databricks Workflows | Docker | Drift Detection | Embeddings | FastAPI | Feature Pipelines | Function Calling | Hybrid search | Injection Defense | LLM Observability | Langchain | Langgraph | Language Models | Large Language Models | Latency SLO | Model Serving | Model versioning | Monitoring | Observability | OpenTelemetry | PII handling | Prompt engineering | Prompt injection | Prompt injection defense | Python | RAG | Red Teaming | Retrieval-Augmented Generation | Serverless Application Model | Terraform | Testing | Token Telemetry | Tool use | Vector Search
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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