Senior AI Engineer
Tasks
- Add structured logging and distributed tracing
- Build REST APIs and inference endpoints
- Build vector search pipelines
- Collaborate on AI roadmap
- Design LLM integration pipelines
- Detect data drift
- Develop structured output validation
- Implement Retrieval-Augmented Generation architectures
- Implement human in the loop review workflows
- Implement model performance monitoring
- Integrate AI services with backend microservices
- Optimize retrieval quality
- Serve machine learning models in production
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AWS | Anthropic API | Azure | B testing | Circuit Breakers | Cohere | Data Drift | Data Drift Detection | Distributed tracing | Drift Detection | Embeddings | GCP | GRPC | Go | Graceful Degradation | Input validation | Kafka | Kinesis | Langchain | Latency SLO | Latency monitoring | Learning operations | Llamaindex | MLflow | Machine Learning | Machine Learning Operations | Model Performance Monitoring | Model performance | Node.js | OpenAI API | PGVector | Performance Monitoring | Pinecone | PostgreSQL | Prompt engineering | Prompt versioning | Python | RAG | REST API | Retrieval-Augmented Generation | SageMaker | Structured Logging | Vector Database | Vertex AI | Weaviate | Weights and Biases
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Roles
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