Generative AI Engineer – Azure

Introduction: As a Generative AI Engineer specializing in Microsoft Azure, you will be responsible for developing and deploying cutting-edge GenAI solutions for enterprise use cases, particularly within the financial services industry. You will work closely with a team of technical experts to integrate AI capabilities into existing systems and applications, leveraging the power of Large Language Models (LLMs) and other advanced AI technologies.

Responsibilities:

• Develop and implement Generative AI solutions using Microsoft Azure AI services.
• Collaborate with stakeholders to understand business requirements and design AI applications that meet specific needs.
• Integrate AI models with enterprise data sources, databases, and internal systems.
• Participate in the full Software Development Life Cycle (SDLC) from requirements analysis to deployment and maintenance.
• Ensure the security and compliance of AI applications through DevSecOps best practices.
• Conduct unit testing, integration testing, debugging, and troubleshooting of AI applications.
• Stay up-to-date on the latest AI technologies and trends to continuously improve GenAI solutions.

Required Skills and Qualifications:

• Minimum 8+ years of overall IT experience in software development, engineering, or related roles.
• At least 3 years of hands-on experience in Generative AI development.
• Minimum 5+ years of experience with Microsoft Azure environments and Azure AI services.
• Proven experience developing GenAI solutions for financial services or regulated industries.
• Strong programming skills in Python and/or other relevant languages.
• Experience with Large Language Models (LLMs) and AI application integration.
• Understanding of AI security, data privacy, and governance.
• Knowledge of DevSecOps practices and CI/CD pipelines.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications:

• Experience delivering GenAI solutions in financial services or similar enterprise environments.
• Knowledge of AI security, responsible AI practices, and data privacy.
• Experience deploying and monitoring AI applications in Azure cloud environments.
• Experience working in Agile development teams.

Note: Local candidates are strongly preferred. Candidates must be willing to work onsite. Relocation candidates may be considered.