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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist-Advanced Analytics - **Company:** IBM - **Location:** Armonk, NY, United States (Remote available) - **Contract:** Permanent contract - **Skills:** LangGraph Framework, AI Evaluation, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Cluster Analysis, Software Code Optimization, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, NoSQL, NumPy, Tensorflow, SAP (Applications), SQL Databases, Workflow Management Systems, Jupyter Notebook, Enterprise Software Applications, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Agentic-AI, Pandas, Containerization, AI Platforms, Scikit Learn, CrewAI, AutoGen, Machine Learning Operations, Claude, Azure AI, Model Context Protocol, Semantic Kernel, GPT, Databricks, Programming Languages - **Published:** October 3, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/lxl73lsphw ## About the Role * Design and implement agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar platforms. * Build and orchestrate multi-agent workflows, integrating AI agents with enterprise applications, APIs, and data sources. * Develop RAG (Retrieval-Augmented Generation) solutions using vector databases, embeddings, and enterprise knowledge repositories. * Fine-tune, evaluate, and optimize foundation models and LLM-based applications. * Programming Languages: Exposure to programming languages, particularly Python, and development environments like PyCharm, VS Code, and Jupyter Notebooks * SAP Ecosystem for EAM Preferred Education None Required Technical And Professional Expertise Required Professional and Technical Expertise Generative & Agentic AI * LLMs (GPT, Claude, Llama, Mistral, etc.) * Prompt Engineering and RAG * Agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel) * Multi-agent orchestration and workflow design * MCP (Model Context Protocol) and agent integration patterns * AI evaluation, observability, and governance Traditional AI & Data Science * Machine Learning and Deep Learning * Statistical Modeling and Predictive Analytics * NLP, Classification, Clustering, Time Series Forecasting * Feature Engineering and Model Optimization * Python (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow) Preferred Technical And Professional Experience Enterprise Asset Management * Knowledge of SAP ecosystem will be preferred Data & Cloud Technologies * SQL, NoSQL, Vector Databases * Data Engineering and ETL/ELT concepts * Azure AI, Databricks, AWS, or GCP AI Services * MLOps / LLMOps, CI/CD, Containerization ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Vectorize all the things! 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