Data Scientist-Advanced Analytics

IBM; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

IBM Consulting is seeking experts to build and deploy generative and agentic AI solutions across enterprise environments in the United States. You will design agentic AI systems, orchestrate multi-agent workflows, and integrate AI agents with APIs and data sources to deliver impactful business outcomes.

The role emphasizes RAG implementations, LLM evaluation, and governance, with hands-on coding in Python and experience with frameworks like LangGraph, CrewAI, AutoGen, and Semantic Kernel.

Qualifications

• Must have experience with generative and agentic AI systems.
• Proficiency with large language models (GPT, Claude, Llama, etc.).
• Strong skills in prompt engineering and retrieval-augmented generation (RAG).
• Familiarity with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel).
• Knowledge of AI evaluation, governance, and observability practices.

Responsibilities

• Develop and deploy machine learning, deep learning, and generative AI solutions.
• Design and implement agentic AI systems and multi-agent workflows.
• Integrate AI agents with enterprise apps, APIs, and data sources.
• Build RAG solutions using vector databases and embeddings.
• Fine-tune and evaluate foundation models and LLM-based apps.
• Code in Python and use tools like PyCharm or VS Code.

Skills

Generative AI

Agentic AI

LLMs

Prompt Engineering

RAG

Python

Tools

LangGraph

CrewAI

AutoGen

Semantic Kernel

Job description

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

• Develop and deploy machine learning, deep learning, and generative AI solutions.
• 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

Preferred Education

None

Required Technical And Professional 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

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