Mid level GenAI Engineers
Tasks
- Add guardrails policy filters PII redaction runtime monitors and agent observability
- Apply prompt engineering for use cases
- Build GenAI and agentic systems
- Collaborate with clients and stakeholders
- Deliver end-to-end GenAI solutions
- Develop MLOps production deployments for models
- Implement LLM evaluation and continuous data quality
- Implement chunking hybrid search vector stores re ranking feedback loops and eval
- Select integrate finetune LLMs and multimodal models
- Write unit tests and document GenAI results
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent Orchestration | Autogen | Azure | CrewAI | Deep learning | Google Cloud | Guardrails | Human-in-the-loop | Hybrid search | LLM Evaluation | Langchain | Langgraph | Langsmith | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Natural Language | Natural Language Processing | Open Source | Open-source Models | OpenAI Gym | PII Redaction | Pinecone | Prompt engineering | Python | Qdrant | Re-ranking | Runtime Monitoring | SQL | Semantic Kernel | The Loop | Vector Database
Education
N/A
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