Mission
Define and validate enterprise-grade AI solution architectures, with mandatory strength in AI architecture and Azure Cloud architecture. The AI Architect ensures alignment between business objectives, solution design, enterprise architecture and implementation constraints.
Key Responsibilities
Define end-to-end architecture for AI, GenAI, Copilot, Agentic AI, and data-driven solutions.
Provide architecture oversight across the solution lifecycle, from requirements through deployment and operations.
Review solution designs, technical specifications, and implementation approaches to ensure alignment with enterprise architecture standards.
Conduct architecture reviews and hands-on code reviews, ensuring quality, performance, security, scalability, and maintainability.
Guide development teams on AI/ML frameworks, cloud-native architectures, APIs, integrations, and engineering best practices.
Establish reference architectures, reusable design patterns, and development standards.
Support technology selection, proof-of-concepts, and technical risk mitigation.
Collaborate with business stakeholders, product owners, data scientists, and engineering teams to translate business requirements into technology solutions.
Ensure compliance with security, governance, responsible AI, and data privacy standards.
Required Skills & Experience
10+ years of experience in solution architecture, software engineering, or enterprise application development.
3+ years of experience designing and delivering AI/GenAI solutions.
Strong hands-on experience with Python, APIs, microservices, cloud-native applications, and modern software engineering practices.
Experience with Azure AI, Azure OpenAI, Azure ML, Databricks, or equivalent platforms.
Knowledge of RAG architectures, LLMs, vector databases, AI agents, and MLOps.
Strong understanding of CI/CD, DevSecOps, software quality, and design patterns.
Proven experience performing architecture governance, code reviews, and technical mentoring.