Be Part Of A High-Performing Risk Technology Team:

This opportunity sits within a leading global financial institution’s Risk Technology division, supporting enterprise-scale initiatives across market and credit risk platforms. The team operates at the intersection of advanced analytics, artificial intelligence, and large-scale data engineering, enabling smarter decision-making and operational efficiency across the organization.

The Risk Technology group is known for delivering secure, scalable, and forward-thinking solutions within a highly regulated financial environment. With a focus on innovation and modernization, the team is actively integrating generative AI, conversational AI agents, and intelligent automation into enterprise systems. The environment is collaborative, fast-paced, and deeply technical—bringing together AI engineers, data engineers, application developers, and risk stakeholders to build next-generation AI capabilities on Azure.

What’s In Store For You:

• Exposure to enterprise-grade AI initiatives within a global banking environment.
• Opportunity to design and deploy cutting-edge generative AI and conversational AI solutions.
• Collaboration with cross-functional teams across Risk, Engineering, and Application Development.
• Engagement in high-visibility AI transformation programs with real business impact.

How You Will Make An Impact:

• Design, develop, and deploy intelligent conversational AI solutions leveraging Azure AI technologies and Databricks.
• Build and manage enterprise-grade AI agents to support automation and advanced conversational use cases.
• Develop reusable AI components and pipelines within Azure AI Studio and Databricks for scalable deployment.
• Integrate AI services into web and enterprise applications using Python frameworks such as FastAPI, Django, and Flask.
• Create secure RESTful APIs, async workers, and SDK-based integrations for AI services.
• Architect and maintain secure MLOps pipelines including model registry controls, deployment security, and runtime monitoring.
• Monitor and optimize LLM and NLP model performance for reliability, scalability, and accuracy.
• Ensure compliance with data privacy, security, and enterprise governance standards.
• Collaborate with business and technology teams to design conversational flows and scalable AI architectures.

Are You a Proven AI Engineering Leader in Enterprise Azure Environments?

• 10+ years of experience in software engineering, AI engineering, or machine learning engineering roles.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Proven hands-on experience with Azure AI services including Azure OpenAI, Azure AI Studio, Azure Bot Service, Cognitive Services, and Copilot.
• Strong experience with Databricks (including Databricks Genie) and enterprise AI agent development.
• Deep understanding of NLP, LLM architectures, prompt engineering, and model evaluation techniques.
• Strong Python programming skills with experience in FastAPI, Django, or Flask.
• Experience building secure REST APIs and integrating AI services into enterprise applications.
• Expertise in MLOps including CI/CD, model deployment, monitoring, and runtime security in Azure environments.
• Experience with Azure Machine Learning and Azure DevOps/GitHub CI/CD pipelines.
• Familiarity with MCP for secure AI integration with external APIs and tools.
• Strong understanding of enterprise security, governance, and compliance requirements.

Preferred:

• Microsoft Certified: Azure AI Engineer Associate (or equivalent).
• Databricks Certified: Generative AI Engineer Associate (or equivalent).
• Experience with prompt lifecycle management and AI model governance.
• Experience working in financial services or other regulated industries.
• Strong communication skills and ability to operate in cross-functional agile teams.