AI Architect

Experience level 10+ Years.
At least 5 years of experience in implementing cloud-based AI workloads on Azure, delivering production grade solutions.
Bachelor’s Degree in any of Computer Science, Statistics, Data Science or a related field.
At least 2 year of experience in implementing Azure OpenAI solutions.
Generative AI, Deep Learning, Machine learning, LLMOps.
LLM Experience in prompting & fine tuning in GPT3.5/Turbo, GPT-4/4o is a must. Experience in other LLMs would be a plus.
Certifications in AI/ML technologies and Cloud platforms, such as Azure AI Engineer Associate (AZ-102).
Certification in Azure Solutions Architect Expert and other cloud platforms e.g. AWS, Google would be a plus.
Programming experience in one of the languages – Python, R, Java, C#.
Cloud Services Expertise: Azure OpenAI, Document Intelligence, AI Search, Cosmos DB, App service, Managed Identities, Customer Managed Keys, Azure IaaS and PaaS solutions, Copilot Studio.
Experience in CI/CD Tools Bitbucket, Terraform is a must.
Experience gathering non-functional requirements, performing designed and validated application architecture frameworks, and executing functional, stress and performance testing.
Strong knowledge of business analysis, requirement gathering, and gap analysis.
Strong communication, presentation, and interpersonal skills.
Fast learner, individual as well as a team player and can work under pressure.

Translate the business requirements for AI applications into viable AI solutions within Azure.
Select appropriate Azure technologies, considering deployment models and their seamless integration with existing tools.
Partner with Enterprise Architecture, Application Development, and Business teams to design pilot projects and develop production-ready solutions.
Gather feedback from diverse stakeholders to ensure that the technical implementation aligns with both current and future AI requirements.
Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI usage and compliance.
Gain an understanding of and contribute to LLM operations, focusing on the infrastructure and operational capabilities required to deploy Azure AI solutions.
Develop tools and capabilities that support data ingestion, feature engineering, data management, and organization.
Integrate security best practices into solutions to facilitate streamlined CI/CD pipelines for deployment and secure software delivery.
Establish the Azure OpenAI service in Microsoft Azure with an architecture tailored to support business teams.

No preferred qualifications provided.