Senior AI Architect - Enterprise Integrations

IBM

Remote

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Work type
Remote
Location
Remote
Posted
12 days ago

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Similar $207k
$151k most similar roles pay here $274k

This listing doesn't post a salary. Most similar roles pay $168,787–$246,150.

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

IBM currently has 704 open roles on FindRole.

Listed pay typically runs $1,000,000–$1,000,000 across 9 roles with salary data.

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At a glance

TL;DR · Senior AI Architect - Enterprise Integrations

As a Senior AI Architect in the Enterprise Integrations team based in Los Angeles, you will lead the design and implementation of advanced AI solutions that integrate seamlessly with existing enterprise systems. Your day-to-day responsibilities include collaborating with cross-functional teams to identify business needs, architecting scalable machine learning models, and ensuring robust integration with cloud platforms like AWS and Azure. You will leverage Python and Java for developing intelligent workflows, utilize Kubernetes for container orchestration, and work extensively with TensorFlow and PyTorch for model training and deployment. This role requires a deep understanding of AI/ML principles, strong experience in software engineering practices, and the ability to tackle complex business challenges at scale within an enterprise environment.

What you'll do

  • Design and implement advanced AI solutions for enterprise clients.
  • Integrate AI systems with existing enterprise infrastructure securely.
  • Optimize AI models to improve performance and scalability in production.
  • Conduct technical reviews and provide guidance on AI architecture.
  • Stay updated with the latest AI technologies and industry trends.

What we're looking for

  • 5+ years of experience in designing and implementing AI solutions for enterprise clients.
  • Proven track record of leading technical teams in delivering complex AI projects.
  • Expertise in machine learning frameworks such as TensorFlow or PyTorch.
  • Strong background in data engineering, including ETL processes and big data technologies.
  • Experience with cloud platforms like AWS, Azure, or Google Cloud for AI deployments.
  • Excellent communication skills to interface effectively with both technical and non-technical stakeholders.

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