AI Technology Ecosystem Architect

IBM

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Work type: On-site
Location: Raleigh, NC
Posted: 10 days ago

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Similar $202k

$153k most similar roles pay here $251k

This listing doesn't post a salary. Most similar roles pay $162,375–$241,600.

Based on 240 similar postings.

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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 8 roles with salary data.

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TL;DR · AI Technology Ecosystem Architect

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As an AI Technology Ecosystem Architect at a leading tech company in Raleigh, NC, you will join a dynamic team of experts to design and implement advanced solutions using foundation models and large language models. Your primary responsibilities include architecting scalable AI ecosystems that integrate cutting-edge technologies such as machine learning frameworks, cloud services, and data analytics tools. You will work closely with cross-functional teams to identify business needs and develop innovative solutions that drive operational efficiency and enhance user experiences. Proficiency in Python, Java, and Kubernetes is essential, along with expertise in natural language processing and distributed systems. This role demands a deep understanding of AI technologies and their applications across various industries, enabling you to tackle complex challenges at scale and deliver impactful results.

Skills

AI LLM Python TensorFlow PyTorch Kubernetes Docker CI/CD AWS Azure GCP PostgreSQL MongoDB Git Jenkins Prometheus Grafana

What you'll do

Design and implement scalable AI solutions using foundation models and large language models.
Integrate diverse data sources to enhance model performance and accuracy.
Develop innovative applications leveraging AI technologies for business impact.
Maintain up-to-date knowledge of advancements in AI and machine learning.
Ensure security and privacy compliance in all AI ecosystem projects.

What we're looking for

Minimum 5 years of experience in designing and implementing AI technology ecosystems.
Proven expertise in foundation models and large language models (LLMs).
Strong background in cloud computing platforms like AWS, Azure, or GCP.
Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Excellent knowledge of data engineering practices and big data technologies.
Demonstrated ability to lead cross-functional teams in AI project development.

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