Related skills
python mlops pyspark llms rag📋 Description
- Build agentic workflows with LangChain/LangGraph and similar frameworks.
- Develop autonomous agents for data validation, reporting, and docs.
- Deploy scalable agent pipelines with monitoring and evaluation.
- Develop GenAI apps using GPT, Gemini, and LLaMA; implement RAG.
- Build distributed data pipelines (Python, PySpark) and APIs.
- Collaborate with data scientists to productionize POCs.
🎯 Requirements
- 8-12 years in AI/ML, data science, or software; 4+ years GenAI.
- Strong Python, PySpark, API development experience.
- LangChain/LangGraph, Transformers, OpenAI/Vertex/Bedrock SDKs.
- Experience building AI agents, retrieval pipelines, tool calls.
- GenAI concepts: prompting, embeddings, RAG, evaluation, context.
- Cloud (Azure/AWS/GCP), Docker, and ML CI/CD experience.
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