As an AI Engineer – Partner Ecosystem, you will work at the intersection of artificial intelligence, technical enablement, and strategic partnerships. This role is instrumental in driving AI adoption, empowering partners with AI technologies, and fostering collaboration on AI-driven solutions. You will act as a trusted advisor, providing technical guidance, hands-on support, and best practices to help partners successfully integrate AI into their products and services.
Key Responsibilities
Partner Enablement & AI Adoption
- Educate partners on AI technologies, frameworks, and industry best practices.
- Conduct AI-focused workshops, webinars, and training sessions to upskill partner teams.
- Provide comprehensive technical guidance on AI integration, deployment, and optimization.
- Assist partners in leveraging AI/ML for their specific business use cases.
- Enable partners to make data-driven decisions through AI-powered insights.
AI Solution Development & Integration
- Work closely with partners to design, develop, and implement AI-driven solutions.
- Assist in integrating machine learning (ML), natural language processing (NLP), and computer vision into partner products.
- Customize AI models to align with partner-specific needs and business goals.
- Ensure the scalability, security, and performance of AI solutions within partner ecosystems.
- Collaborate with IBM’s AI research and development teams to bring cutting-edge innovations to partners.
Technical Support & Troubleshooting
- Provide hands-on technical support throughout the AI development lifecycle.
- Troubleshoot AI-related challenges, ensuring smooth model integration and deployment.
- Work in tandem with IBM’s internal AI teams to address and resolve partner-specific technical issues.
- Assist partners in optimizing AI model performance for real-world applications.
Collaboration & Relationship Management
- Build and nurture strong relationships with IBM technology partners and stakeholders.
- Act as a liaison between IBM’s AI teams and external partner organizations.
- Gather feedback from partners and relay valuable insights to improve IBM AI solutions.
- Align AI solutions with evolving industry trends and partner business objectives.
AI Research & Innovation
- Stay updated with the latest AI advancements, tools, and frameworks.
- Experiment with cutting-edge AI models to provide innovative solutions.
- Contribute to the continuous enhancement of AI capabilities within IBM’s partner ecosystem.
- Participate in AI-focused conferences, meetups, and industry discussions.
Compliance, Ethics & Responsible AI
- Ensure all AI solutions align 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.
- Advocate for responsible AI usage in partner solutions.
Required Technical and Professional Expertise
AI & Machine Learning Frameworks
- Strong understanding of AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Hands-on experience with large-scale AI models, including Generative AI, LLMs, and reinforcement learning.
- Knowledge of edge AI solutions and AI model optimization for various deployment environments.
Programming & Development Skills
- Proficiency in Python for AI development.
- Experience working with AI-driven APIs and SDKs to facilitate partner integrations.
- Familiarity with DevOps/MLOps pipelines, CI/CD workflows for AI models, and automation tools.
- Understanding of cloud-based AI services and their integration into AI solutions.
- Experience with Kubernetes, Docker, and serverless AI deployments.
Data Engineering & AI Infrastructure
- Knowledge of big data processing frameworks such as Apache Spark, Hadoop, and Databricks.
- Experience in building and managing scalable AI/ML data pipelines.
- Understanding of various database technologies, including SQL, NoSQL, and GraphDBs.
AI Analytics & Monitoring
- Familiarity with AI observability and monitoring tools to track model performance.
- Experience in AI explainability, bias detection, and continuous model optimization.
- Ability to fine-tune AI models for optimal accuracy and efficiency.
Preferred Technical and Professional Experience
- Extensive experience in AI/ML, deep learning, and data science, including Generative AI.
- Expertise in cloud-based AI services from major providers (AWS, Azure, Google Cloud, IBM Cloud).
- Strong background in MLOps, AI deployment strategies, and model lifecycle management.
- Exceptional problem-solving, communication, and technical enablement skills.
- Ability to work cross-functionally with internal and external stakeholders.
Preferred Education
- Bachelor’s degree in Computer Science, AI, Data Science, or a related field.
- Master’s degree or relevant certifications in AI/ML is a plus.
Why Join IBM?
- Drive meaningful AI transformations across industries.
- Collaborate with a global network of AI experts and engineers.
- Work on cutting-edge AI models and solutions that shape the future.
- Gain hands-on experience with the latest AI technologies and frameworks.
If you are passionate about AI, partner engagement, and driving technical enablement, we encourage you to apply and be a part of IBM’s AI revolution!