AI-ML Enterprise Architect : Newark, NJ : Only local

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Deepika Dua

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May 18, 2026, 10:00:03 AM (yesterday) May 18
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Greetings,

Please carefully read the Job Description below, and if you would like to pursue this opportunity, please email me an updated MS Word version of your resume to Deep...@VBeyond.com at your earliest convenience.  If you're not interested feel free to send me your resume and let me know what type of positions, I can help you with. I appreciate your time and look forward to hearing from you. 

 

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Position: AI-ML Enterprise Architect

Location: Newark, NJ

Type Long term Contract

 

Job Description:

Role Purpose

Define enterprise AI/ML platform patterns and standards, create ML Ops frameworks and templates, establish model governance standards, and provide the patterns that enable consistent, responsible, scalable deployment of AI/ML capabilities. This role focuses on creating ML patterns and standards, not building individual models.

What Makes This Role Unique

GenAI integration architect: Lead the enterprise approach to LLM and GenAI integration with RAG patterns, vector databases, and prompt engineering standards

ML Ops framework creator: Design the ML Ops templates that enable consistent model deployment across the organization

Responsible AI champion: Embed ethics, bias detection, and explainability into ML patterns from the start

Emerging technology: Shape how the organization adopts cutting-edge AI/ML technologies

 

Key Responsibilities

Enterprise ML Standards & Patterns (40%)

  • Define ML platform reference architectures (training, serving, monitoring)
  • Create MLOps patterns and templates (ML pipeline templates, CI/CD templates for models, model versioning and registry patterns)
  • Establish model governance framework (approval process, versioning standards, lineage tracking, performance monitoring standards)
  • Define feature store patterns and feature engineering standards
  • Document model deployment patterns (real-time API, batch inference, streaming, embedded)
  • Create GenAI/LLM integration patterns (RAG architecture templates, LLM API integration patterns, prompt engineering standards, vector database patterns)
  • Establish model monitoring and observability standards (drift detection, performance metrics)

ML Frameworks & Templates (35%)

  • Build ML project templates for common use cases (classification, regression, NLP, computer vision)
  • Create model serving templates (REST API, batch scoring, streaming inference)
  • Define responsible AI framework (bias detection and mitigation patterns, model explainability standards, ethical AI guidelines, model documentation templates)
  • Establish data preparation patterns for ML (feature engineering, data labeling, synthetic data)
  • Document ML experimentation standards (experiment tracking, hyperparameter tuning)

Roadmap & Coordination (15%)

  • Develop AI/ML platform modernization roadmap
  • Define GenAI and LLM adoption strategy
  • Coordinate with Data Platform team on ML data pipeline patterns
  • Evaluate ML platform technologies and provide recommendations

Governance & Enablement (10%)

  • Train solution architects and data scientists on ML patterns
  • Review ML solution architectures for pattern compliance
  • Participate in AI governance and ethics reviews
  • Maintain ML pattern catalog

Required Qualifications

Education:

Bachelor’s degree in computer science, Data Science, Machine Learning, or related field

 

Experience:

  • 7+ years in machine learning, AI architecture, or data science
  • 5+ years creating ML platform architectures and MLOps frameworks
  • Proven experience deploying ML models at production scale
  • Experience with GenAI/LLM integration and RAG architectures
  • Track record establishing model governance and responsible AI practices

 

Certifications (Preferred):

  • Cloud ML/AI certification (AWS Machine Learning, Azure AI Engineer, Google Cloud ML Engineer)
  • MLOps certification
  • TOGAF certification

Preferred Qualifications

  • Research publications in ML/AI conferences or journals
  • Experience with large-scale ML systems (billions of predictions/day)
  • Deep expertise in GenAI and LLM architectures
  • Track record implementing responsible AI and model governance at scale
  • Experience in regulated industries requiring model explainability

 

 

Regards,
Deepika Dua

VBeyond Corporation

https://www.linkedin.com/in/deepika-dua-018459166/

E: Deep...@vbeyond.com | www.vbeyond.com

390 Amwell Road, Suite # 107, Hillsborough, NJ 08844

 


Note – VBeyond is fully committed to Diversity and Equal Employment Opportunity.

 

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