Senior Applied AI Engineer
Tasks
- Build prompting context engineering and tool usage systems
- Deploy low latency inference services
- Design and build LLM powered product features used in production
- Develop agentic workflows and frameworks
- Develop evaluation frameworks for LLM and agent performance
- Implement RAG retrieval augmented generation architectures
- Improve reliability latency and cost efficiency of AI pipelines
Perks/Benefits
Skills/Tech-stack
Apache Kafka | CI/CD | Context engineering | Embeddings | Evaluation | Experiment tracking | FastAPI | Go | Inference Optimization | Inference Server | Kubernetes | Language Models | Large Language Models | Model Monitoring | Model versioning | NVIDIA Triton | NVIDIA Triton Inference Server | Prompt engineering | Python | Retrieval-Augmented Generation | Semantic Search | Transformers | Triton Inference Server | Vector Database | Vector Search
Education
N/A
Roles
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