Data Engineer (1059)

Jersey City - hybrid onsite

contract to hire

W2 only

Role Overview

We are seeking an experienced AI/ML Engineer to design, build, and operationalize modern AI solutions on Azure. This is a hands-on, AI-first role focused on generative AI, intelligent agents, and machine learning - turning enterprise data (including messy, unstructured sources) into structured, searchable, and actionable insight.

You'll build and deploy real GenAI applications: LLM-powered chatbots and agents, retrieval-augmented generation (RAG) pipelines, vector search, and workflows that extract structure from unstructured documents. Strong Python and data engineering fundamentals on Azure underpin the work.

Key Responsibilities

Generative AI & Agents

• Design and build LLM-powered applications, chatbots, and AI agents using models such as Claude and Gemini
• Implement RAG pipelines - chunking, embeddings, vector search, and retrieval orchestration
• Build tool-calling and task-automation agents integrated with enterprise data sources and APIs
• Develop pipelines that read unstructured files (e.g., PDFs) and convert them into structured, queryable data
• Deploy AI services as REST/serving endpoints; implement evaluation, monitoring, and observability

Machine Learning

• Support the end-to-end ML lifecycle: feature engineering, training, inference, and model management
• Collaborate with data scientists and stakeholders to translate business problems into AI-driven solutions

Data Engineering (Azure)

• Build and maintain scalable data pipelines in Azure using Python, PySpark, and SQL
• Ingest data from APIs, streaming platforms, and enterprise systems
• Ensure data quality, lineage, and governance across pipelines

DevOps & Delivery

• Implement CI/CD (Azure DevOps / GitHub) across DEV, QA, and PROD environments
• Enforce security, governance, and compliance controls; monitor pipelines and AI workloads

Required Qualifications

• ~5 years of AI/ML experience
• Strong hands-on Python, PySpark, and SQL
• Solid Azure experience
• Demonstrated experience building GenAI/LLM applications - chatbots, agents, RAG, vector search/embeddings
• Experience converting unstructured data (e.g., PDFs) into structured formats
• Solid grounding in data engineering, data modeling, and pipeline development

Preferred Qualifications

• Experience with Databricks (Notebooks, Workflows, DLT, Delta Lake, Unity Catalog)
• Databricks AI/BI (Genie, Lakeview dashboards, semantic models) and Agent Framework / Agent Bricks
• MLflow, Mosaic AI / model serving
• Azure data stack (ADF, ADLS, Synapse) and Power BI integration
• Medallion (Bronze/Silver/Gold) architecture

Nice to Have

• Experience in cybersecurity or enterprise data platforms
• Knowledge of data governance, masking, and regulatory compliance
• Experience building executive dashboards or analytics platforms

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