Mid level GenAI Engineers
Tasks
- Add runtime monitoring and agent observability
- Apply prompt engineering
- Build NLP and CV solutions
- Build agentic systems
- Collaborate with stakeholders
- Deploy models to production using MLOps
- Document results
- Evaluate LLM systems
- Implement chunking and hybrid search
- Implement guardrails policy filters and PII redaction
- Select integrate and fine tune LLMs
- Use vector stores and re ranking
- Write unit tests for GenAI solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Autogen | Azure | Computer Vision | CrewAI | Deep learning | Google Cloud | Guardrails | Hybrid search | LLM Evaluation | Langchain | Langgraph | MLOps | Machine Learning | NLP | Observability | Open Source | Open-source Models | PII Redaction | Pinecone | Prompt engineering | Python | Qdrant | Re-ranking | SQL | Semantic Kernel | Vector Database
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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