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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