Job description:

Azure AI Engineer \\r\\n\\r\\nRole Description \\r\\n\\r\\nThis resource will be joining Windows team, collaborating with various sectors within infrastructure like Security and Networking to create, launch, and support AI based cloud and hybrid applications. Given the collaborative requirements of this position, it is essential that the candidate possesses advanced Gen AI/Azure/technical skills alongside strong interpersonal abilities. The candidate should demonstrate a strong blend of technical skill and industry knowledge and exhibit excellent communication, teamwork, customer service, and leadership qualities to effectively engage with cloud engineering, Power Platform engineering team, information security, and line of business teams. \\r\\n\\r\\nResponsibilities \\r\\n\\r\\nTranslate the business requirements for AI applications into viable AI solutions within Azure \\r\\n\\r\\nSelect appropriate Azure technologies, considering deployment models and their seamless integration with existing tools \\r\\n\\r\\nPartner with Enterprise Architecture, Application Development, and Business teams to design pilot projects and develop production-ready solutions \\r\\n\\r\\nGather feedback from diverse stakeholders to ensure that the technical implementation aligns with both current and future AI requirements \\r\\n\\r\\nWork closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI usage and compliance \\r\\n\\r\\nGain an understanding of and contribute to LLM operations, focusing on the infrastructure and operational capabilities required to deploy Azure AI solutions \\r\\n\\r\\nDevelop tools and capabilities that support data ingestion, feature engineering, data management, and organization \\r\\n\\r\\nIntegrate security best practices into solutions to facilitate streamlined CI/CD pipelines for deployment and secure software delivery \\r\\n\\r\\nEstablish the Azure OpenAI service in Microsoft Azure with an architecture tailored to support business teams \\r\\n\\r\\nPreferred Qualifications and Skills \\r\\n\\r\\nAt least 5 years of experience in implementing cloud-based AI workloads on Azure, delivering production grade solutions \\r\\n\\r\\nBachelor\\'s Degree in any of Computer Science, Statistics, Data Science or a related field \\r\\n\\r\\nAt least 1 year of experience in implementing Azure OpenAI solutions \\r\\n\\r\\nGenerative AI, Deep Learning, Machine learning, LLMOps \\r\\n\\r\\nLLM Experience in prompting & finetuning in GPT3.5/Turbo, GPT-4/4o is a must. Experience in other LLMs would be a plus. \\r\\n\\r\\nCertifications in AI/ML technologies and Cloud platforms, such as Azure AI Engineer Associate (AZ-102) \\r\\n\\r\\nCertification in Azure Solutions Architect Expert and other cloud platforms e.g. AWS, Google would be a plus. \\r\\n\\r\\nPrograming experience in one of the languages - Python, R, Java, C# \\r\\n\\r\\nCloud Services Expertise: Azure OpenAI, Document Intelligence, AI Search, Cosmos DB, App service, Managed Identities, Customer Managed Keys, Azure IaaS and PaaS solutions, Copilot Studio \\r\\n\\r\\nExperience in CI/CD Tools Bitbucket, Terraform is a must. \\r\\n\\r\\nExperience gathering non-functional requirements, performing designed and validated application architecture frameworks, and executing functional, stress and performance testing \\r\\n\\r\\nStrong knowledge of business analysis, requirement gathering, and gap analysis \\r\\n\\r\\nStrong communication, presentation, and interpersonal skills \\r\\n\\r\\nFast learner, individual as well as a team player and can work under pressure \\r\\n\\r\\nPower Automate development experience would be a plus

• Depending on the work environment, the subject matter expert may lead or be an active participant of a work-group with the need for specialized knowledge.
• Meet all agreed-upon turnaround times for deliverables, deliverable