Gen AI
Tasks
- Automate root cause analysis with multi agent systems
- Build AI driven diagnostic tools for job failures and SLA breaches
- Build multi-agent systems
- Correlate operational data across AWS and Databricks
- Deploy and maintain LLM applications
- Design data pipelines for generative AI solutions
- Develop human in the loop agent workflows
- Document AI agent architectures and data pipeline integrations
- Evaluate and select generative AI architectures
- Fine tune and optimize LLMs for domains
- Implement AI guardrails and security protocols
- Implement LLM observability and hallucination detection
- Integrate LLMs with RAG frameworks
- Orchestrate workflows with LangChain and LangGraph
- Prevent prompt injection
- Protect sensitive data
- Update prompt chains iteratively
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agent systems | Airflow | Asynchronous programming | Attention Mechanisms | Databricks | Delta Lake | Docker | Fine Tuning | Google ADK | Human-in-the-loop | Injection Protection | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | LoRA | MLflow | Mosaic AI | Multi-Agent | Multi-Agent Systems | PEFT | Pandas | Prometheus | Prompt engineering | Prompt injection | Prompt-injection protection | PySpark | Python | RAG | Retrieval-Augmented Generation | Security | The Loop | Transformer Models | Vector Databases
Education
N/A
Roles
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