AI Engineer C2C AI Azure Foundry at Newark, NJ

Job Title:

AI Engineer with AI Azure Foundry

Location:

Newark, NJ
Duration:
Contract

An Azure AI Foundry AI Engineer designs, builds, and deploys intelligent generative AI, agentic workflows, and RAG (Retrieval-Augmented Generation) applications. This role requires coding with Python, orchestrating AI models, and adhering to responsible AI standards for enterprise scalability.

• AI & Agent Development:
  Design autonomous or semi-autonomous AI agents and RAG pipelines using Azure AI Foundry.
• Model Orchestration & Integration:
  Build and fine-tune large language models (LLMs) and integrate them with business applications, Copilot Studio, and data pipelines.
• Testing & Evaluation:
  Implement performance and evaluation tooling such as RAGAS or Tru Lens to assess grounding accuracy, reduce hallucinations, and ensure model explainability.
• Infrastructure Management:
  Develop scalable AI infrastructure and maintain reusable AI components in accordance with engineering best practices (version control, observability, CI/CD).

Technical

Skills:

Proficiency in Python, prompt engineering, and utilizing frameworks like Lang Chain, Semantic Kernel, or crewAI.

Cloud

Experience:

Deep understanding of the Microsoft Azure ecosystem, including Azure OpenAI Service, Azure Machine Learning, and Microsoft Fabric.

AI Governance: Strong focus on Responsible AI and Model Context Protocol (MCP) to ensure security, privacy, and fairness in model outputs.

Experience: Typically requires a bachelor’s degree in computer science or a related field, alongside 2-5+ years of software or AI/ML engineering experience.

• Python (primary language)
• ML frameworks:
  Tensor Flow, PyTorch, Scikit-learn
• Data pipelines and preprocessing
• Model deployment and MLOps (e.g., MLflow, Docker, CI/CD)
• Machine learning, deep learning, and statistics
• Data modeling and feature engineering
• APIs and microservices
• Cloud platforms (Azure ML, Sage Maker, Vertex AI)
• LLMs (GPT, Llama, etc.)
• RAG (Retrieval-Augmented Generation)
• Prompt engineering and vector databases
• Ability to build AI-powered applications (chatbots, agents, copilots).