AI Solution Architect – Azure AI Foundry

Position: AI Solution Architect – Azure AI Foundry

Experience: 10–15+ years overall IT experience with 5+ years in AI/ML, GenAI, or AI solution architecture

Location: Hyderabad

Employment Type: Full-Time

Role Overview: We are looking for an experienced AI Solution Architect with strong hands-on expertise in Generative AI, Large Language Models (LLMs), Azure AI Foundry, Azure OpenAI, RAG, and Agentic AI .

The candidate will be responsible for architecting enterprise-grade AI solutions on Microsoft Azure, translating business requirements into scalable AI architectures, and guiding engineering teams from proof of concept through production deployment.

The ideal candidate should combine AI/GenAI expertise, Azure cloud architecture, software engineering, data architecture, security, and strong stakeholder-management skills .

Key Responsibilities

AI Solution Architecture

• Design end-to-end enterprise GenAI and AI solutions using Azure AI services.
• Define scalable, secure, reliable, and cost-effective AI architectures.
• Translate business requirements and use cases into technical AI solutions.
• Evaluate AI models, frameworks, tools, and technologies and recommend appropriate solutions.
• Create architecture diagrams, technical designs, POCs, and reference architectures.
• Establish architecture standards and best practices for AI application development.

Azure AI Foundry & Azure OpenAI

• Lead implementation of solutions using Azure AI Foundry .
• Design and deploy applications using Azure OpenAI Service and foundation models.
• Work with Azure AI Search, Azure Machine Learning, Azure Storage, Azure Functions, and other Azure services.
• Establish appropriate model selection, deployment, security, and governance strategies.
• Optimize AI workloads for performance, scalability, reliability, and cost.

Generative AI, RAG & Agentic AI

• Architect RAG (Retrieval-Augmented Generation) solutions using enterprise data.
• Design AI Agent and Agentic AI architectures, including multi-agent workflows where appropriate.
• Define approaches for embeddings, vector search, semantic retrieval, and knowledge grounding.
• Design prompt engineering and context-management strategies.
• Evaluate LLMs based on accuracy, latency, cost, security, and business requirements.
• Design LLM evaluation and monitoring strategies.

Data & Integration Architecture

• Define data architecture required for AI/GenAI applications.
• Integrate structured and unstructured enterprise data with AI solutions.
• Design APIs, microservices, event-driven integrations, and enterprise application interfaces.
• Work closely with data engineering teams on data pipelines and data quality.
• Experience with Microsoft Fabric, Azure Data Factory, Databricks, or equivalent is an advantage.

AI Security & Responsible AI

• Define security architecture for enterprise AI applications.
• Implement data privacy, access control, encryption, and secure API integration.
• Establish AI governance, responsible AI, and compliance practices.
• Address risks such as prompt injection, data leakage, hallucination, and unauthorized model access.
• Define guardrails and content-safety mechanisms for GenAI applications.

DevOps & Productionization

• Define CI/CD strategies for AI applications.
• Work with Docker, Kubernetes, Git, and Azure DevOps/GitHub .
• Establish deployment, monitoring, logging, and observability practices.
• Guide teams in moving AI POCs into scalable production solutions.
• Define operational processes for model and application lifecycle management.

Leadership & Stakeholder Management

• Work with business leaders, product owners, engineering teams, data scientists, and cloud architects.
• Lead technical discussions and architecture reviews.
• Mentor AI/ML engineers and development teams.
• Communicate complex AI concepts clearly to technical and non-technical stakeholders.
• Provide technical leadership across multiple AI initiatives.

Mandatory Technical Skills

AI / GenAI

• Generative AI
• Large Language Models (LLMs)
• RAG
• Agentic AI / AI Agents
• Prompt Engineering
• Embeddings
• Vector Search / Vector Databases
• LLM Evaluation
• AI Guardrails
• Responsible AI

Microsoft Azure

• Azure AI Foundry
• Azure OpenAI Service
• Azure AI Search
• Azure Machine Learning
• Azure Functions
• Azure App Services
• Azure Storage
• Azure Cloud Architecture

Pro…