Azure AI Foundry SME
Visionet Systems Inc. · Bengaluru, Karnataka, India
- On site
- Full-time
- $120,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Implement Agentic AI platform using Azure AI Foundry.
- Deploy Azure OpenAI, AI Search, and Vector DBs.
- Manage AI models, endpoints, and security.
- Support agent deployment pipelines and RAG optimization.
- Develop reusable AI components and best practices.
About the role
Azure AI Foundry SME
Role Summary:
Implement an Agentic AI platform using the Azure AI Foundry ecosystem, enabling model provisioning, orchestration, governance, and enterprise deployment patterns.
Responsibilities:
- Setup and configure Azure AI Foundry workspaces.
- Deploy Azure OpenAI, Azure Search, Vector DBs, and Purview integration.
- Develop re-usable Azure AI Foundry components and best practices for RAG and Agentic AI.
- Manage models, endpoints, versioning, security, and cost controls.
- Support agent deployment pipelines and MCP registry integration.
- Assist in RAG optimization, re-rankers, and prompt flows.
- Automate the Agentic AI platforms scaffolding.
Skills:
- Azure AI Foundry, Azure OpenAI, AI Search, Content Safety
- Azure Monitor, Purview, RBAC, Key Vault
- Prompt engineering & model management best practices
Key skills/competency:
- Azure AI Foundry SME
- Agentic AI Platform Implementation
- Azure OpenAI
- Azure AI Search
- Vector Databases
- Prompt Engineering
- Model Management
- Azure Governance
- DevOps for AI
- Enterprise AI Deployment
Skills & topics
- Azure AI Foundry
- Azure OpenAI
- AI Search
- Agentic AI
- Prompt Engineering
- Model Management
- Vector Databases
- Azure Governance
- Cloud AI
- SME
How to get hired
- Tailor your resume: Highlight experience with Azure AI Foundry, Azure OpenAI, and AI Search. Quantify achievements in AI platform implementation.
- Showcase expertise: Emphasize skills in prompt engineering, model management, and Azure governance in your application.
- Prepare for technical questions: Be ready to discuss RAG optimization, agent deployment, and AI security best practices.
- Research Visionet Systems: Understand their focus on AI solutions and enterprise deployment to align your application.
Technical preparation
Master Azure AI Foundry workspace setup.,Practice Azure OpenAI and AI Search deployments.,Build RAG systems and optimize prompt flows.,Implement AI model versioning and security.
Behavioral questions
Describe a complex AI platform challenge.,How do you ensure AI governance and security?,Share your experience with cross-functional teams.,How do you stay updated on AI trends?
Frequently asked questions
- What specific Azure AI Foundry experience is required for this Azure AI Foundry SME role at Visionet Systems?
- This Azure AI Foundry SME position at Visionet Systems requires hands-on experience setting up and configuring Azure AI Foundry workspaces, deploying core components like Azure OpenAI and Azure AI Search, and developing reusable components and best practices within the ecosystem.
- How does Visionet Systems use Azure OpenAI and AI Search in their Agentic AI platform implementation?
- Visionet Systems leverages Azure OpenAI for generative AI capabilities and Azure AI Search for intelligent information retrieval as part of their Agentic AI platform. This SME role will be instrumental in integrating and optimizing these services.
- What are the key responsibilities for an Azure AI Foundry SME at Visionet Systems regarding model management and deployment?
- The Azure AI Foundry SME at Visionet Systems will be responsible for managing AI models, endpoints, versioning, ensuring security, and controlling costs. They will also support agent deployment pipelines and MCP registry integration.
- Can you provide more details on the 'agent deployment pipelines' mentioned for the Azure AI Foundry SME role?
- Support for agent deployment pipelines involves ensuring smooth and automated processes for deploying AI agents. This includes integration with CI/CD practices and potentially MCP registry for model and agent version control.
- What is the expected level of involvement in RAG optimization for this Azure AI Foundry SME position?
- The Azure AI Foundry SME will actively assist in RAG (Retrieval-Augmented Generation) optimization. This includes working with re-rankers, prompt flows, and fine-tuning retrieval mechanisms to improve AI response accuracy and relevance.
- What other Azure services are relevant for the Azure AI Foundry SME at Visionet Systems?
- Beyond Azure AI Foundry and Azure OpenAI, relevant services include Azure AI Search, Vector Databases, Azure Monitor for performance tracking, Purview for data governance, RBAC for access control, and Key Vault for security.
- Is this Azure AI Foundry SME role at Visionet Systems remote or on-site?
- While the job description doesn't explicitly state the work arrangement, similar roles at technology companies often offer flexibility. It is recommended to inquire about remote, hybrid, or on-site options during the application process.