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

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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.

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

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TL;DR · Senior AI Architect - Enterprise Integrations

As a Senior AI Architect in the Enterprise Integrations team based in East Wenatchee, you will lead the technical delivery of advanced AI solutions tailored for large enterprises. Your day-to-day responsibilities include designing and implementing scalable machine learning models, integrating AI systems with existing enterprise infrastructure, and collaborating closely with cross-functional teams to solve complex business problems. You will leverage cutting-edge technologies such as TensorFlow, PyTorch, and Kubernetes, while also working extensively with Python and Java. Ideal candidates possess strong experience in cloud platforms like AWS or Azure, along with a deep understanding of data engineering practices and machine learning algorithms. This role is crucial for driving innovation within our enterprise-scale products, focusing on areas like predictive analytics and automated decision-making systems.

What you'll do

  • Design and implement advanced AI solutions for enterprise integration.
  • Lead technical architecture reviews to ensure scalability and reliability.
  • Develop machine learning models tailored to business needs.
  • Integrate AI systems with existing enterprise infrastructure securely.
  • Optimize data flow and processing within AI applications.

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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