What are the responsibilities and job description for the Artificial Intelligence Engineer position at Infyshine, Inc?
Job Description
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
• Python (primary language)
ML frameworks: TensorFlow, PyTorch, Scikit-learn
Data pipelines and preprocessing
Model deployment and MLOps (e.g., MLflow, Docker, CI/CD) [indeed.com]
Machine learning, deep learning, and statistics
Data modeling and feature engineering
APIs and microservices
Cloud platforms (Azure ML, SageMaker, Vertex AI)
LLMs (GPT, Llama, etc.)
RAG (Retrieval-Augmented Generation)
Prompt engineering and vector databases
Ability to build AI-powered applications (chatbots, agents, copilots)
Linked in URL is mandatory
Microsoft Certified: Azure AI Engineer Associate or the Azure AI Apps and Agents Developer Associate will be given priority compared to other candidates. If the candidate is certified, request to include the respective Microsoft Certification link in the resume (without that certificate credentials are not accepted).
Experience Required: 8-10
Required Skills: TensorFlow, PyTorch, Scikit-learn, llms, MLOps, cloud, RAG, my sql