AI Engineering Lead

Brobston Group; Nutley (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

Brobston Group in Nutley, NJ seeks an AI Engineering Lead to define and operationalize data architecture, governance, and platform strategy to accelerate enterprise AI initiatives. You will enable trusted, secure, reusable data assets and collaborate across engineering, governance, security, and product teams to advance adoption.

The role emphasizes building scalable data platforms on Azure and Databricks, establishing data quality and lineage, and mentoring high-performing teams to deliver

Qualifications

• Extensive experience in enterprise data engineering and large-scale data architectures.
• Expertise with Azure data services, Databricks, and Lakehouse patterns.
• Strong data governance, quality, lineage, and metadata practices.
• Experience enabling AI/ML through governed data foundations, including vector-ready approaches and RAG.
• Proven engineering leadership, mentoring, and cross-team collaboration to ensure platform reliability.

Responsibilities

• Define enterprise data architecture standards and cloud-native platform strategies.
• Oversee data readiness and onboarding for AI use cases with reusable data products.
• Establish data quality, metadata, cataloging, stewardship, and compliance standards.
• Lead CI/CD and DataOps for scalable ingestion, streaming, and transformation services.
• Align AI and data organizations, mentor teams, and influence stakeholders.

Skills

Enterprise data engineering

Cloud data platforms

Distributed systems

Large-scale data architecture

Azure data services

Databricks

Lakehouse architecture

Delta Lake

ETL/ELT pipelines

Streaming pipelines

Data governance

Data quality

Metadata & lineage

Semantic modeling

Data product frameworks

AI/ML data foundations

Vector-ready architectures

RAG

Unstructured data processing

Engineering leadership

Stakeholder influence

Platform reliability

Education

Bachelor’s or Master’s degree in a relevant technical discipline

Tools

Azure

Databricks

Delta Lake

Lakehouse

Job description

Summary

The AI Engineering Lead defines and operationalizes enterprise data architecture, governance, and platform strategy to support scalable AI, analytics, and digital initiatives. This leader enables trusted, secure, reusable, AI-ready data assets and works across engineering, governance, architecture, security, and product teams to advance enterprise AI adoption.

Responsibilities

• Define enterprise data architecture standards and cloud-native platform strategies using Azure, Databricks, and modern distributed data frameworks.
• Lead data readiness and onboarding for AI use cases, developing reusable data products and validating quality, lineage, governance, and operational readiness.
• Establish standards for data quality, metadata, cataloging, stewardship, retention, compliance, and platform observability.
• Oversee scalable data ingestion, streaming, transformation, and engineering services while driving CI/CD, DataOps, testing, and operational excellence.
• Align AI and data organizations, advise business and technology leaders, and build and mentor high-performing engineering teams.

Requirements

• Bachelor’s or master’s degree in a relevant technical discipline, or equivalent experience.
• Significant experience in enterprise data engineering, cloud data platforms, distributed systems, and large-scale data architecture.
• Expertise in Azure data services, Databricks, Lakehouse architecture, Delta Lake, and scalable ETL/ELT and streaming pipelines.
• Strong knowledge of data governance, quality, lineage, metadata, semantic modeling, and reusable data product frameworks.
• Experience enabling AI and machine learning through governed data foundations, with understanding of vector-ready architectures, RAG, and unstructured data processing.
• Demonstrated engineering leadership, team development, stakeholder influence, and focus on platform reliability and operational excellence.