AI/ML Platform Architect

Job Title – AI/ML Platform Architect

Job Location Newark, NJ  -Onsite from day one - (May go to 3 days once onboarded) -Need to be local

Duration - 6 Months+

Visa  - Any Visa except H1B,CPT

Rate -  W2 

Mode Of Interview -  Phone/Skype

Note – Need LinkedIn

eading U.S. Healthcare Enterprise

Level:

Senior / Principal

Work Schedule:

3 days/week from office

Description

We are seeking an experienced AI/ML Platform Architect to define enterprise AI/ML architecture standards, MLOps frameworks, and GenAI integration patterns. This role focuses on building scalable AI platform blueprints, governance models, and reusable ML patterns—not developing individual ML models.

The ideal candidate will have deep expertise in MLOps, LLM/GenAI architectures, Responsible AI, and enterprise-scale ML platform design.

Role and Responsibilities

Enterprise AI/ML Architecture

• Define enterprise ML platform reference architectures and standards

• Design reusable MLOps frameworks, CI/CD pipelines, and model deployment templates

• Establish model governance, lineage, monitoring, and observability standards

• Create scalable model serving patterns for batch, streaming, and real-time inference

• Define feature store and feature engineering standards

GenAI & LLM Enablement

• Design enterprise GenAI/LLM integration patterns

• Create RAG architecture templates and vector database standards

• Define prompt engineering and LLM integration best practices

Responsible AI & Governance

• Establish Responsible AI standards including:

o Bias detection and mitigation

o Model explainability

o Ethical AI guidelines

• Participate in AI governance and architecture review boards * Develop AI/ML platform modernization roadmap

* Evaluate AI/ML technologies and recommend enterprise standards

* Mentor architects, ML engineers, and data scientists on enterprise AI patterns

Core Skills & Qualifications

Experience

* 7+ years in AI/ML, Data Science, or ML Architecture

* 5+ years designing enterprise ML platforms and MLOps frameworks

* Strong experience with production-scale ML deployments

* Hands-on experience with GenAI, LLMs, and RAG architectures

* Experience implementing Responsible AI and model governance frameworks

Technical Skills

* ML Platforms: SageMaker, Azure ML, Vertex AI, Databricks

* MLOps & Model Serving: MLflow, Kubeflow, Seldon, KFServing, TensorFlow Serving

* GenAI & LLMs: RAG, Vector Databases, Prompt Engineering

* Governance: Model monitoring, drift detection, lineage, explainability

* Cloud & Containers: AWS/Azure/Google Cloud Platform, Kubernetes, Docker

Preferred Certifications

* AWS/Azure/Google Cloud Platform AI/ML Certifications

* TOGAF

* MLOps Certification

Success Metrics

* Standardize enterprise MLOps adoption across AI teams

* Publish reusable AI/ML and GenAI architecture patterns

* Improve governance and compliance for production ML models

* Accelerate scalable and responsible AI adoption enterprise-wide