Principal AI Engineer
Tasks
- Add observability for LLM workflows
- Build RAG pipelines
- Build and evaluate proof of concepts for agents
- Design generative AI solutions using LLMs
- Develop agent-based architectures
- Develop multi step reasoning flows
- Evaluate GenAI performance using metrics
- Experiment with agent orchestration patterns
- Implement prompt versioning and prompt testing
- Implement task planning for agents
- Implement tool usage for agents
- Integrate LLMs into enterprise applications using APIs
- Perform offline evaluations for LLMs
- Research emerging GenAI and agent frameworks
- Translate research ideas into implementations
Perks/Benefits
- N/A
Skills/Tech-stack
API Integration | AWS Bedrock | Agent Orchestration | CI/CD | Deep learning | Docker | Elasticsearch | Faiss | Few-Shot Prompting | Few-shot | GitHub Actions | Hallucination control | Hugging Face | JSON | Knowledge Base | Knowledge Base Search | LLMOps | Language Models | Large Language Models | Logging | Memory systems | Monitoring | NLTK | Offline evaluation | OpenSearch | Pinecone | Planning | PostgreSQL | Prompt engineering | Prompt testing | Prompt versioning | Python | RAG | Reflection | Retrieval-Augmented Generation | Schema Based Outputs | Spacy | Streamlit | Structured prompting | Tool-Calling | Transformers | Vector Databases
Education
N/A
Roles
AI Developer | AI Engineer | Applied AI Engineer | Data Scientist | Developer | Engineer | Generative AI Developer | Lead | Lead Data | Lead Data Scientist | Principal | Principal AI Engineer | Scientist
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