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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

As a Data Scientist specializing in Artificial Intelligence and agentic systems, you will architect, develop, and deliver advanced AI solutions that leverage foundation models, large language models (LLMs), and modern agentic frameworks. You will work across the full lifecycle of AI projects—from research and prototyping to production deployment—focusing on building autonomous, reasoning‑driven systems that operate reliably in complex enterprise environments. You will apply strong software engineering practices, deep machine learning expertise, and an understanding of both structured and unstructured data to create robust, scalable, and integrated AI capabilities.

This role is cloud‑agnostic but requires solid experience deploying AI systems on cloud platforms and integrating them with enterprise services, APIs, and data sources.

Responsibilities

• Design and build AI and agentic solutions using foundation models, LLMs, and modern agentic frameworks

• Implement multi‑step autonomous reasoning workflows and agent orchestration for real enterprise use cases

• Develop production‑grade Python code including APIs and backend components using frameworks such as FastAPI

• Work with ML and NLP frameworks such as PyTorch, TensorFlow, Keras, Hugging Face, and classical ML libraries

• Build and refine models for structured and unstructured data, including NLP, image, video, and voice processing

• Integrate AI solutions with enterprise systems, APIs, databases, and data pipelines

• Deploy, monitor, and maintain AI workloads in cloud environments using containerization and orchestration

• Implement best practices in model evaluation, observability, explainability, and responsible AI

• Support CI/CD workflows, testing, model versioning, and secure configuration management

• Collaborate with cross‑functional teams to translate business challenges into cognitive computing solutions

• Document architectures, design decisions, data flows, and operational runbooks

Required education

Bachelor's Degree

Preferred education

Master's Degree

Required technical and professional expertise

• 5+ years of experience as a Data Scientist, Machine Learning Engineer, or AI Engineer

• Hands‑on experience designing and implementing agentic AI solutions

• Strong expertise in Python for AI development, including backend frameworks

• Proficiency with LLMs, foundation models, and relevant frameworks such as Hugging Face, LangChain, and LangGraph

• Strong foundation in ML and NLP techniques for structured and unstructured data

• Experience with ML frameworks including PyTorch, TensorFlow, and Keras

• Experience with relational and NoSQL databases such as SQL, Postgres, and MongoDB

• Practical experience deploying AI solutions in cloud environments

• Familiarity with containerization and orchestration using Docker and Kubernetes

• Experience across the full AI lifecycle from research to production deployment

• Strong software engineering practices including version control, testing, code quality, and documentation

Preferred technical and professional experience

• Experience with autonomous agent‑to‑agent communication patterns

• Familiarity with emerging standards such as Model Context Protocol

• Experience with orchestration and workflow tools for AI agents

• Knowledge of authentication and authorization protocols such as OIDC and OAuth

• Experience with CI/CD pipelines and DevOps practices for ML and AI systems

• Experience using coding assistants such as GitHub Copilot or CodeWhisperer

Soft Skills

• Strong analytical and systems‑thinking skills

• Ability to communicate complex AI concepts to technical and non‑technical audiences

• Ability to lead technical decisions in AI architecture and agentic system design

• Collaborative mindset and ability to work in dynamic multi‑disciplinary teams

• Strong ownership and focus on delivering production‑grade solutions