Mid level GenAI Engineers
Tasks
- Add runtime monitoring and observability
- Build GenAI/agentic systems
- Collaborate with stakeholders
- Deploy models in production
- Develop prompt engineering for use cases
- Document results
- Evaluate LLM performance
- Implement PII redaction
- Implement chunking and hybrid search
- Implement feedback loops
- Integrate vector stores and re ranking
- Perform unit testing for GenAI solutions
- Select integrate and fine tune LLMs
- Set up guardrails and policy filters
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent Orchestration | Autogen | Azure | Chunking | Computer Vision | CrewAI | Deep learning | GCP | Human-in-the-loop | Hybrid search | LLM | LLM Evaluation | Langchain | Langgraph | Langsmith | Language Processing | MLOps | Machine Learning | NLP | Natural Language | Natural Language Processing | Pinecone | Prompt engineering | Python | Qdrant | Re-ranking | SQL | Semantic Kernel | The Loop | Vector Database | Vector Search
Education
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