[Hiring] AI Solutions Engineer @ISACA

Role Description

The AI Solutions Engineer is responsible for the development, integration, implementation, and maintenance of 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

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence, or a related field.
• 5+ years of professional software or application development experience, including hands-on experience developing applications or solutions from 0 to 1, and experience developing, implementing, or integrating LLM enabled applications.
• Strong software development foundation plus hands-on LLM enabled application experience, with the more specialized AI/LLM/cloud experience remaining preferred.
• Experience integrating applications with APIs, enterprise systems, databases, or other data sources.
• Experience developing or supporting applications within a cloud-based environment.
• Experience applying security and data protection practices to application development and system integrations.

Requirements

• Advanced degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field (preferred).
• 8+ years of professional software or application development experience, including two (2) or more years of hands-on experience developing, implementing, or integrating AI, generative AI, LLM-powered, or agentic AI solutions (preferred).
• Experience developing or integrating AI and LLM solutions within a complex or enterprise environment.
• Experience with Microsoft Azure, Azure OpenAI, Azure AI services, or comparable cloud-based AI platforms.
• Experience developing agentic AI workflows and orchestrating AI models, tools, APIs, and data sources.
• Experience with retrieval-augmented generation (RAG), prompt engineering, embeddings, semantic search, or vector databases.
• Experience implementing security controls and safeguards for AI-enabled applications.
• Experience developing evaluation or monitoring approaches for AI application performance, accuracy, hallucinations, or model drift.
• Experience optimizing LLM prompts, model configurations, or parameters for performance, reliability, and cost efficiency.
• Experience working within a complex, enterprise, international, or global organization.

Benefits

• ISACA Career Opportunities and Benefits