Introduction

At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Your role and responsibilities

An AI Engineer focused on the partner ecosystem works at the intersection of artificial intelligence (AI), business partnerships, and technical enablement. This role is responsible for driving AI adoption, enabling partners with AI tools, and collaborating on AI-driven solutions. Below are the key responsibilities:

1. Partner Enablement & AI Adoption

* Educate partners on AI technologies, frameworks, and best practices.

* Conduct workshops, webinars, and training sessions to upskill partners on AI models and tools.

* Provide technical guidance and resources to help partners integrate AI into their solutions.

* Support partners in understanding AI/ML development, deployment, and optimization.

2. AI Solution Development & Integration

* Collaborate with partners to design, develop, and implement AI-powered solutions.

* Assist partners in integrating AI models (e.g., machine learning, NLP, computer vision) into their products.

* Support the customization of AI models for partner use cases.

* Ensure scalability, security, and efficiency in AI deployments within partner ecosystems.

3. Technical Support & Troubleshooting

* Provide hands-on technical support for partners during AI development and deployment.

* Troubleshoot AI-related issues, ensuring smooth integration with partner platforms.

* Work closely with internal AI teams to address partner challenges.

4. Collaboration & Relationship Management

* Build and maintain strong relationships with technology and business partners.

* Act as a bridge between internal AI teams and external partners.

* Gather feedback from partners and relay insights to improve AI offerings.

* Align AI solutions with partner business objectives and industry trends.

5. AI Research & Innovation

* Stay updated on the latest AI trends, tools, and best practices.

* Experiment with emerging AI models and frameworks to provide innovative solutions for partners.

* Collaborate with AI researchers and developers to enhance AI capabilities.

6. Compliance, Ethics & Responsible AI

* Ensure AI solutions comply with ethical AI principles and industry regulations.

* Advise partners on AI governance, data privacy, and compliance requirements.

* Promote fairness, transparency, and accountability in AI deployments.

Required education

Bachelor's Degree

Preferred education

Bachelor's Degree

Required technical and professional expertise

AI & Machine Learning Frameworks

Proficiency in AI/ML libraries
Experience working with large-scale AI models (e.g., LLMs, generative AI, reinforcement learning).
Knowledge of edge AI and AI model optimization for different deployment environments.

Programming & Development Skills, Strong coding skills in Python
Experience with AI-driven APIs and SDKs for partner integrations. Knowledge of DevOps/MLOps pipelines, CI/CD for AI, and automation tools

Experience with AI/ML services from major cloud providers:

Familiarity with Kubernetes, Docker, and serverless AI deployments.

Data Engineering & AI Infrastructure

Knowledge of big data processing frameworks (Apache Spark, Hadoop, Databricks).
Experience with data pipelines, feature engineering, and model training at scale.
Understanding of database technologies (SQL, NoSQL, GraphDBs)

AI Analytics & Monitoring

Familiarity with AI observability and monitoring tools (
Experience in model explain ability and AI performance tuning.

Preferred technical and professional experience

* Strong experience in AI/ML, deep learning, and data science including Generative AI

* Proficiency in Python, TensorFlow, PyTorch, or other AI frameworks.

* Knowledge of cloud AI services

* Experience with MLOps, AI deployment, and model optimization.

* Excellent communication and technical enablement skills.

* Ability to work cross-functionally with internal teams and external partners.