Azure AI Solution Architect

Role Overview:
We are seeking an experienced Solution Architect – AI & Azure Cloud to design, evaluate, and implement enterprise-scale AI and cloud solutions. The ideal candidate will drive AI proof-of-concepts (POCs), define scalable Azure architectures, and guide the transition of innovative solutions into production. You will work closely with business stakeholders, architects, developers, security teams, and product owners to deliver secure, scalable, and cloud-native solutions.

Key Responsibilities:
Research and evaluate emerging AI technologies, foundation models, AI agents, orchestration frameworks, and cloud platforms.
Design end-to-end Azure-based solution architectures aligned with enterprise standards.
Build and validate AI Proof of Concepts (POCs) and transition successful solutions into production.
Design cloud-native applications, APIs, integrations, automation workflows, and data platforms.
Integrate GenAI solutions with existing applications, APIs, and enterprise data pipelines.
Ensure production readiness through robust error handling, logging, monitoring, resiliency, and observability.
Develop architecture documentation, technical designs, standards, and implementation roadmaps.
Conduct architecture reviews and ensure compliance with security, governance, and enterprise best practices.
Collaborate with cross-functional teams throughout the Software Development Lifecycle (SDLC).
Mentor engineering teams on Azure, AI architecture, and modern software engineering practices.
Participate in Agile ceremonies, code reviews, and technical design discussions.

Required Skills:
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
10+ years of software engineering and solution architecture experience.
5+ years of hands-on experience designing enterprise solutions on Microsoft Azure.
Strong experience with Azure services such as Azure OpenAI, Azure Functions, API Management, Azure Storage, Azure SQL, AKS, Azure AI Search, and Azure DevOps.
Experience evaluating emerging AI technologies and delivering AI Proof of Concepts (POCs).
Hands-on experience implementing Generative AI, LLMs, AI Agents, RAG, or AI orchestration frameworks.
Strong understanding of cloud-native architecture, microservices, REST APIs, and integration patterns.
Experience developing APIs using FastAPI or similar frameworks.
Experience with CI/CD pipelines, Git, Azure DevOps, or GitHub Actions.
Strong understanding of production engineering concepts including logging, monitoring, resiliency, fault tolerance, retry mechanisms, and observability.
Excellent analytical, problem-solving, communication, and stakeholder management skills.
Experience working in Agile/Scrum environments and leading technical discussions.

Preferred Skills:
Experience with AI orchestration frameworks such as LangChain, Semantic Kernel, or AutoGen.
Knowledge of container platforms such as Docker and Azure Kubernetes Service (AKS).
Experience with enterprise integration patterns and API management.
Microsoft Azure certifications such as AZ-305 (Azure Solutions Architect Expert), AI-102 (Azure AI Engineer), AZ-204, or related certifications are preferred.