Dimension Data

2 weeks ago

AI Engineer (Commercial & MTO)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Build production-ready AI and machine learning solutions that drive revenue generation, market analysis, and make-to-order (MTO) supply chain performance. Partner with business leaders and product managers to identify high-impact AI/ML use cases, then deploy models into scalable APIs and operational pipelines. Develop multi-agent and RAG workflows to optimize MTO/e-commerce logistics, manage unstructured data pipelines, and continuously monitor model accuracy, reliability, and cost in live environments.

Location: Dallas

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Collaborate with business leaders and product managers to map challenges to high-impact AI/ML use cases.
•Deploy trained machine learning models into robust, scalable production-ready APIs integrated with enterprise systems.
•Build multi-agent AI systems, workflows, and RAG architectures to optimize Make-To-Order (MTO) production pipelines and e-commerce supply chains.
•Develop and manage infrastructure to collect, clean, and transform unstructured data for model consumption.
•Maintain and continuously optimize deployed models for accuracy, reliability, and cost-efficiency in production.

Key Requirements

•7+ years of advanced coding skills in Python, SQL, and Java/Scala.
•Proficiency with ML frameworks such as PyTorch or TensorFlow, and workflow frameworks like LangChain.
•5+ years deploying ML models using AWS, Azure, or Google Cloud (GCP) with CI/CD pipelines.
•Ability to explain complex AI outputs to C-suite executives and non-technical stakeholders.
•Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.

Experience:10+ years

Education:Bachelor's in Computer Science, Data Science, Artificial Intelligence, or a closely related quantitative field

Skills:CollaborationBusiness acumenStakeholder communicationContinuous optimization

Certifications:SOC 2 Type II

Tech Stack:PythonSQLJavaScalaPyTorchTensorFlowLangChainAWSAzureGoogle Cloud (GCP)CI/CDRetrieval-Augmented Generation (RAG)APIsMulti-agent systemsMLOps

Company Brief

Dimension Data

Dimension Data, operating under NTT Ltd, provides managed IT services, cloud and data center solutions, networking, cybersecurity, and digital transformation services to enterprise customers worldwide.

Industry: Professional Services

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Public Company (Market Cap in USD)

Headquarters: London, United Kingdom

Founded: 1983

Website LinkedIn

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Dimension Data

2 weeks ago

AI Engineer (Commercial & MTO)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: Dallas

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Collaborate with business leaders and product managers to map challenges to high-impact AI/ML use cases.
•Deploy trained machine learning models into robust, scalable production-ready APIs integrated with enterprise systems.
•Build multi-agent AI systems, workflows, and RAG architectures to optimize Make-To-Order (MTO) production pipelines and e-commerce supply chains.
•Develop and manage infrastructure to collect, clean, and transform unstructured data for model consumption.
•Maintain and continuously optimize deployed models for accuracy, reliability, and cost-efficiency in production.

Key Requirements

•7+ years of advanced coding skills in Python, SQL, and Java/Scala.
•Proficiency with ML frameworks such as PyTorch or TensorFlow, and workflow frameworks like LangChain.
•5+ years deploying ML models using AWS, Azure, or Google Cloud (GCP) with CI/CD pipelines.
•Ability to explain complex AI outputs to C-suite executives and non-technical stakeholders.
•Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.

Experience:10+ years

Education:Bachelor's in Computer Science, Data Science, Artificial Intelligence, or a closely related quantitative field

Skills:CollaborationBusiness acumenStakeholder communicationContinuous optimization

Certifications:SOC 2 Type II

Tech Stack:PythonSQLJavaScalaPyTorchTensorFlowLangChainAWSAzureGoogle Cloud (GCP)CI/CDRetrieval-Augmented Generation (RAG)APIsMulti-agent systemsMLOps

Company Brief

Dimension Data

Industry: Professional Services

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Valuation: Public Company (Market Cap in USD)

Headquarters: London, United Kingdom

Founded: 1983

Website LinkedIn