Senior AI Engineer
Tasks
- Build document ingestion and chunking pipelines
- Build human in the loop review workflows
- Collaborate to define AI roadmap and translate requirements
- Design and maintain vector search pipelines
- Design build maintain production LLM integration pipelines
- Design model retraining workflows data pipelines feature engineering
- Develop and operate AI features for financial products
- Establish prompt versioning and evaluation practices
- Evaluate and integrate AI frameworks and tools
- Implement model performance monitoring and data drift detection
- Implement structured output validation fallback handling confidence scoring
- Instrument AI components with logging tracing and alerting
- Integrate AI services with backend microservices using API contracts and circuit breakers
- Optimize retrieval quality embedding selection reranking and metadata filtering
- Serve ML models in production infrastructure with monitoring
- Write backend code to power AI integrated features
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Anthropic API | Async Programming | Azure | Chain orchestration | Cohere API | Data Drift | Data Drift Detection | Distributed tracing | Drift Detection | Embeddings | GCP | GRPC | Go | Huggingface | Input validation | Kafka | Kinesis | LLM | Langchain | Latency SLO | Llamaindex | MLflow | Machine Learning | Metadata filtering | Model Serving | Monitoring | Node.js | OpenAI API | Output parsing | PGVector | Pinecone | PostgreSQL | Prompt engineering | Python | RAG | REST APIs | Reranking | SageMaker | Structured Logging | Vector Databases | Vertex AI | Weaviate | Weights and Biases
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Roles
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