AI Solutions Engineer

About ISACA ISACA® (www.isaca.org) champions the global workforce advancing trust in technology. For more than 55 years, ISACA has empowered its community of 195,000+ members with the knowledge, credentials, training and network they need to thrive in fields like information security, governance, assurance, risk management, data privacy and emerging tech. With a presence in more than 195 countries and with more than 230 chapters worldwide, ISACA offers resources tailored to every stage of members’ careers—helping them to thrive in a rapidly changing digital landscape, drive trusted innovation and ensure a more secure digital world. Through the ISACA Foundation, ISACA also expands IT and education career pathways, fostering opportunities to grow the next generation of technology professionals. Overview The AI Solutions Engineer is responsible for the development, integration, implementation, and maintenance of artificial intelligence (AI) and large language model (LLM) applications used to support internal business operations. This position develops AI-enabled applications, integrations, and tools and connects AI capabilities with existing enterprise systems and data sources. The position works with business and technology teams to translate functional requirements into technical solutions and supports AI applications throughout the development lifecycle, including design, development, testing, deployment, maintenance, and enhancement. The AI Solutions Engineer also ensures solutions are developed in accordance with applicable information security, privacy, data governance, and technology standards. Responsibilities AI and Agentic Solution Development Design, develop, test, deploy, and maintain LLM-powered applications, integrations, and agentic AI solutions using Azure cloud technologies, Azure OpenAI, and related AI services. Develop Python-based applications and services that support natural language processing, generative AI, and other AI-enabled business use cases. Design and implement agentic workflows that orchestrate AI services, models, tools, and internal or external data sources to address defined business requirements. Develop and implement retrieval-augmented generation (RAG), prompt engineering, semantic search, embeddings, and related techniques to support AI application functionality. Develop reusable application components, services, and technical patterns to support AI capabilities across internal applications. Develop prototypes and proofs of concept and transition approved solutions into production applications. AI Integration, Performance and Optimization Integrate Azure OpenAI APIs, AI services, and external models with internal applications, systems, and data sources. Design and maintain integrations with consideration for application reliability, scalability, performance, and maintainability. Develop and optimize prompts, model configurations, and parameters to improve application performance, response quality, and cost efficiency. Perform model configuration and fine-tuning, as appropriate, based on application requirements and available technologies. Monitor, troubleshoot, and debug agentic workflows, application integrations, and AI-generated outputs. Evaluate changes in LLM and AI technologies and recommend modifications or enhancements to existing applications and technical approaches. AI Monitoring, Security & Reliability Develop and implement automated evaluation methods and frameworks to monitor the quality, accuracy, reliability, and performance of AI-enabled applications. Monitor and evaluate AI-generated outputs for hallucinations, performance degradation, and other quality or reliability concerns. Implement technical safeguards to mitigate prompt injection, inappropriate or harmful outputs, unauthorized access, and exposure of confidential or sensitive organizational data. Develop AI solutions in accordance with organizational information security, privacy, data governance, and technology requirements. Work with Information Security and other applicable functions to identify and address technical risks associated with AI applications and agentic workflows. Support ongoing monitoring and maintenance of AI solutions to identify and resolve application, model, integration, and performance issues. Cross Functional Collaboration & Solution Design Collaborate with cross-functional business and technology teams to translate business requirements into technical requirements and AI-enabled solutions. Participate in requirements gathering, solution design, technical planning, and implementation activities. Communicate technical requirements, capabilities, limitations, dependencies, and risks to technical and non-technical stakeholders. Coordinate with Information Technology, Information Security, Data, and other applicable teams regarding system integrations, data requirements, security controls, and deployment dependencies. Provide technical input regarding the feasibility and implementation requirements of proposed AI use cases. Technical Documentation Create and maintain technical documentation for application code, system architecture, integrations, configurations, agentic workflows, and technical dependencies. Document architecture decisions, technical approaches, development standards, and solution configurations to support ongoing maintenance and team knowledge sharing. Maintain documentation as applications, integrations, and technical requirements change. Qualifications Required Field of Study: Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence, or a related field Minimum Years of Experience Required: 5+ years of professional software or application development experience, including hands-on experience developing Python-based applications or solutions, and experience developing, implementing, or int