AI Solutions Engineer

AI Solutions Engineer

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 integrating AI-enabled applications.

Description of Preferred Experience:

• Strong software/Python development foundation plus some hands-on AI-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.

Preferred Field of Study:

• Advanced degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field.

Preferred Years of Experience:

• 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.

Description of Preferred Experience:

• 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

Competencies/Skills Required:

• Strong written and verbal communication skills, with the ability to communicate technical concepts to both technical and non-technical audiences.
• Strong programming and application development skills, including proficiency in Python.
• Working knowledge of artificial intelligence, generative AI, large language models (LLMs), and related development approaches, including prompt engineering, RAG, and agentic workflows.
• Working knowledge of cloud-based technologies, AI services, information security, data privacy, and secure development practices.
• Strong critical thinking, analytical, troubleshooting, and problem-solving skills.
• Ability to translate business requirements into practical, secure, and scalable technical solutions.
• Strong collaboration and stakeholder management skills, with the ability to influence and work effectively across functions without direct authority.
• High degree of initiative, accountability, adaptability, and sound judgment, with the ability to manage multiple priorities and work independently.

This position may require periodic onsite attendance, either currently or in the future, based on business needs. Occasional travel may also be required to attend company-sponsored events, meetings, all-hands gatherings, training sessions, or other activities necessary to support the essential functions of the role.

Equal Opportunity Employer (EEO)

ISACA is proud to be an equal opportunity employer. ISACA is committed to building an environment of diversity, equity, and inclusion where equal employment opportunities are available to all applicants and employees without regard to race, color, religion, sex (including pregnancy and gender identity), national origin, age, ancestry, disability, genetic information, citizenship, sexual orientation, veteran status, marital status, familial status, military discharge status, or any other characteristic or status protected by federal, state, or local law. We support an inclusive workplace where employees excel based on merit, qualifications, experience, and ability.

Posted Salary Range