AI Engineer – Enterprise, Data & AI
Tasks
- Automate multi step business workflows
- Build and deploy intelligent agents
- Build and integrate vector databases
- Design and implement production LLM applications
- Ensure AI accuracy and evaluation
- Fine-tune and evaluate models
- Implement secure tool usage
- Implement security and data privacy standards
- Implement self-healing systems
- Integrate data ingestion pipelines
- Manage model costs
- Optimize latency
- Own AI deployment process
- Perform prompt engineering
- Set up performance monitoring and alerting
- Translate operational bottlenecks into AI automation
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Bedrock | Agentic Workflows | Alerting | Autogen | Autonomous Agents | Cost Management | Data Privacy | Fine Tuning | Google Vertex | Google Vertex AI | Langchain | Latency optimization | Llamaindex | LoRA | Milvus | Model Evaluation | OpenSearch | Performance Monitoring | Pinecone | Prompt engineering | Python | QLoRA | Quantization | RAG | Security | Speculative decoding | Vector Databases | Vertex AI | Weaviate
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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