AI Engineer

AI Engineer

Newark, NJ (No Remote – 3 days in office). Role Overview 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.

Key Responsibilities

• AI & Agent Development:
  Design autonomous or semi-autonomous AI agents and RAG pipelines using Azure AI Foundry (formerly Azure AI Studio).
• 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)

Core Requirements & Skills

• 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 (ClientP) 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)