AI Engineer
Tasks
- Build agentic systems
- Build observability for agent workflows
- Create prompt templates and libraries
- Deploy and monitor LLM systems in production
- Design LLM-powered applications
- Develop RAG pipelines
- Establish prompt testing and versioning
- Evaluate LLM solutions for quality and safety
- Implement multi step orchestration workflows
- Integrate agents with enterprise tools and APIs
- Lead technical discovery and stakeholder communication
Perks/Benefits
- N/A
Skills/Tech-stack
API Security | AWS Bedrock | Agentic AI | Azure | Azure AI | Azure OpenAI | Cloud Native | Embeddings | Fine Tuning | GenAI | Google Vertex | Google Vertex AI | Hugging Face | LLMOps | Language Models | Large Language Models | LoRA | Model Evaluation | OAuth2 | Observability | Orchestration | PEFT | Planning | Prompt engineering | PyTorch | Python | QLoRA | Quantization | RAG | REST APIs | Reasoning | Regression testing | Retrieval-Augmented Generation | TensorFlow | Tool Schemas | Tool-Calling | Vector Databases | Vertex AI
Education
Roles
AI | AI Engineer | Engineer
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