AI Solutions Engineer

ISACA • Remote,

16h • $104,169 - $156,303

About The Position

The AI Solutions Engineer develops, integrates, implements, and maintains large language model (LLM) applications that support internal business operations. The role builds AI-enabled applications, integrations, and tools, connecting AI capabilities with enterprise systems and data sources. It works with business and technology teams to turn functional requirements into technical solutions and supports the full application lifecycle, from design and development through testing, deployment, maintenance, and enhancement. Solutions must follow applicable information security, privacy, data governance, and technology standards.

The engineer designs and implements LLM-powered applications and agentic AI solutions using Azure cloud technologies, Azure OpenAI, and related services. The role also develops Python applications, agentic workflows, retrieval-augmented generation (RAG) capabilities, prompts, semantic search, and reusable components. It integrates AI services and models with internal applications and data, optimizes solution performance and cost, monitors and evaluates outputs, and implements safeguards for security and reliability. The position collaborates across functions, communicates technical considerations to stakeholders, and maintains technical documentation.

Periodic onsite attendance may be required currently or in the future based on business needs. Occasional travel may be required for company-sponsored events, meetings, all-hands gatherings, training, or other activities necessary to support the role.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence, or a related field.
• At least 5 years of professional software or application development experience.
• Hands-on experience developing applications or solutions from 0 to 1.
• Experience developing, implementing, or integrating LLM-enabled applications.
• Experience integrating applications with APIs, enterprise systems, databases, or other data sources.
• Experience developing or supporting applications in a cloud-based environment.
• Experience applying security and data protection practices to application development and system integrations.
• Proficiency in Python and strong programming and application development skills.
• Working knowledge of AI, generative AI, LLMs, and related approaches, including prompt engineering, RAG, and agentic workflows.
• Working knowledge of cloud technologies, AI services, information security, data privacy, and secure development practices.
• Strong written and verbal communication skills, including the ability to communicate technical concepts to technical and non-technical audiences.
• 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, including the ability to influence and work across functions without direct authority.
• Initiative, accountability, adaptability, sound judgment, and ability to manage multiple priorities and work independently.

Nice To Haves

• Advanced degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field.
• At least 8 years of professional software or application development experience, including two or more years developing, implementing, or integrating AI, generative AI, LLM-powered, or agentic AI solutions.
• Experience developing or integrating AI and LLM solutions in 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 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.

Responsibilities

• 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 for 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 business requirements.
• Develop and implement RAG, prompt engineering, semantic search, embeddings, and related techniques.
• Develop reusable application components, services, and technical patterns for AI capabilities across internal applications.
• Develop prototypes and proofs of concept and transition approved solutions into production applications.
• Integrate Azure OpenAI APIs, AI services, and external models with internal applications, systems, and data sources.
• Design and maintain integrations with attention to reliability, scalability, performance, and maintainability.
• Optimize prompts, model configurations, and parameters to improve performance, response quality, and cost efficiency; perform model configuration and fine-tuning as appropriate.
• Monitor, troubleshoot, and debug agentic workflows, integrations, and AI-generated outputs.
• Evaluate changes in LLM and AI technologies and recommend modifications or enhancements to applications and technical approaches.
• Develop and implement automated evaluation methods and frameworks to monitor application quality, accuracy, reliability, and performance.
• Monitor AI-generated outputs for hallucinations, performance degradation, and other quality or reliability concerns.
• Implement safeguards against prompt injection, harmful or inappropriate outputs, unauthorized access, and exposure of confidential or sensitive organizational data.
• Develop solutions in accordance with information security, privacy, data governance, and technology requirements.
• Work with Information Security and other functions to identify and address technical risks associated with AI applications and agentic workflows.
• Support ongoing monitoring and maintenance to identify and resolve application, model, integration, and performance issues.
• Collaborate with 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.
• Communicate technical requirements, capabilities, limitations, dependencies, and risks to technical and non-technical stakeholders.
• Coordinate with IT, Information Security, Data, and other teams on integrations, data requirements, security controls, and deployment dependencies.
• Provide technical input on the feasibility and implementation requirements of proposed AI use cases.
• Create and maintain documentation for code, architecture, integrations, configurations, agentic workflows, and dependencies.
• Document architecture decisions, technical approaches, development standards, and solution configurations; keep documentation current as applications and requirements change.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level