Principal AI Engineer
Tasks
- Build AI evaluation frameworks
- Build reusable agent patterns
- Create RAG pipelines
- Define model fallback behavior
- Design AI system architecture
- Diagnose AI production failure modes
- Ensure production readiness and observability
- Evaluate retrieval quality
- Implement regression testing
- Implement state management and tool calling
- Lead agentic workflow design
- Mentor and review AI designs and prompts
- Package and deploy AI services
- Select and manage LLM models
- Set output quality and reliability metrics
- Translate product requirements into measurable acceptance criteria
Perks/Benefits
Skills/Tech-stack
Autogen | CI/CD | Chroma | CrewAI | Docker | Embeddings | Evaluation | Faiss | FastAPI | Flask | Function Calling | Hallucination detection | Kubernetes | Langgraph | Langsmith | Language Models | Large Language Models | MLflow | Machine Learning | Model Serving | Observability | Ollama | Pinecone | Prompt engineering | Python | REST APIs | Regression testing | Reranking | Retrieval-Augmented Generation | Schema Validation | Semantic Kernel | Semantic Search | Serverless | Structured outputs | TensorRT-LLM | Tool-Calling | VLLM | Vector Databases | Weaviate | Weights and Biases
Education
N/A
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
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