AI Engineer

Role Overview: An Azure AI Foundry AI Engineer designs, builds, and deploys intelligent generative AI, agentic workflows, and RAG (Retrieval-Augmented Generation) applications. Candidate Requirements: Microsoft Certified: Azure AI Engineer Associate or Azure AI Apps and Agents Developer Associate will be given priority compared to other candidates.

Job Title: AI Engineer
Location: Newark, NJ (Hybrid – 3 days onsite)
Duration: 6 months


Salary Range: $56.00 - $58.00/Hour on W2 (Without Benefits).
Applicants must be willing to work on W2

Job Description:
Candidate Requirements:

• Microsoft Certified: Azure AI Engineer Associate or Azure AI Apps and Agents Developer Associate will be given priority compared to other candidates.
• If the candidate is certified, include the respective Microsoft Certification link in the resume. Without that certificate credential, the certification is not accepted.

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 TruLens) 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 LangChain, 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.
• 7+ years in Microsoft Azure.

Programming & Machine Learning:

• Python (primary language).
• ML frameworks: TensorFlow, PyTorch, Scikit-learn.
• Data pipelines and preprocessing.
• Machine learning, deep learning, and statistics.
• Data modeling and feature engineering.

Model Deployment & MLOps:

• Model deployment and MLOps (e.g., MLflow, Docker, CI/CD).

Development & Integration:

• APIs and microservices.

Cloud Platforms:

• Azure ML, SageMaker, Vertex AI.

Generative AI:

• LLMs (GPT, Llama, etc.).
• RAG (Retrieval-Augmented Generation).
• Prompt engineering and vector databases.