AI Engineer

The AI Engineer partners works with product owners, architects, software engineering teams, data teams, security teams, and enterprise application owners to identify high-value AI use cases and translate them into scalable, secure, and maintainable solutions. This role requires software engineering experience, practical knowledge of LLMs and AI application patterns, and the ability to incorporate AI capabilities into existing business systems and workflows.

The incumbent will help evaluate AI technologies, design agent-based workflows, integrate AI services with enterprise platforms, support responsible AI practices, and contribute to the software development lifecycle. Prior experience working with ERP systems and complex enterprise integrations is preferred.

Specific Expected Contributions

• Develops, configures, tests, and supports AI-enabled enterprise application solutions that improve automation, decision support, operational efficiency, and user productivity.
• Collaborates in the development and integration of solutions using large language models, retrieval-augmented generation, agentic workflows, orchestration frameworks, AI services, APIs, and enterprise application platforms.
• Partners with product owners, architects, and technology teams to identify, evaluate, and prioritize AI use cases aligned with business value, risk, feasibility, and technology strategy.
• Translates business needs into functional, technical, and solution design documentation for AI-enabled applications and intelligent automation workflows.
• Configures and supports agentic workflows that can reason over enterprise information, interact with business systems, invoke tools, and support human-in-the-loop review where appropriate.
• Incorporates Model Context Protocol concepts, tool/function calling patterns, API integrations, and secure enterprise connectors into AI-enabled software solutions.
• Builds, enhances, and maintains enterprise software components using object-oriented programming principles and modern application development practices.
• Applies application lifecycle management discipline, including source control, backlog/task management, CI/CD, automated testing, code reviews, release management, and production support practices.
• Works with enterprise application teams to integrate AI capabilities into ERP systems, financial systems, operational platforms, custom applications, and workflow automation solutions.
• Collaborates with data engineering and analytics teams to support AI solution patterns involving structured data, unstructured content, semantic search, knowledge retrieval, data pipelines, and governed enterprise data sources.
• Evaluates AI model behaviors, prompt design, grounding strategies, accuracy, explainability, latency, cost, security, and operational reliability.
• Develops and maintains reusable AI engineering patterns, application components, prompts, evaluation approaches, and technical standards.
• Supports responsible AI practices, including data privacy, security, access control, auditability, transparency, bias mitigation, and appropriate human oversight.
• Collaborates with cybersecurity, infrastructure, and architecture teams to ensure AI-enabled solutions comply with enterprise security, identity, data protection, and governance requirements.
• Troubleshoots and resolves complex issues involving AI application behavior, integrations, data quality, orchestration, application performance, and production incidents.
• Monitors AI-enabled solutions for quality, reliability, user adoption, cost efficiency, performance, and business impact.
• Shares technical knowledge, to software engineering teams adopting AI development patterns.
• Stays current with emerging AI technologies, model capabilities, agent frameworks, AI development tools, enterprise integration patterns, and industry best practices.
• Assists in special projects as required.
• Performs other duties as needed.

• Bachelor’s degree in Computer Science, Information Systems or equivalent experience required., * At least seven (7) years of relevant and progressive work experience in software engineering, enterprise application development, systems integration, data engineering, automation, or related technology disciplines.
• Practical experience designing, developing, integrating, or supporting AI-enabled applications, LLM-based solutions, intelligent automation, or advanced decision-support systems.
• Experience with large language models, prompt engineering, retrieval-augmented generation, embeddings, semantic search, tool/function calling, AI orchestration, or agentic workflow patterns.
• Experience incorporating AI capabilities into enterprise applications, business workflows, operational processes, or internal productivity tools.
• Knowledge of object-oriented programming, software design principles, API development, application integration, and enterprise application architecture.
• Experience with one or more modern programming languages such as .NET/C#, Java, or Python preferred. Comparable experience with other enterprise development languages may be considered.
• Experience with all phases of the software development lifecycle, including requirements analysis, design, development, testing, deployment, monitoring, and production support.
• Experience with application lifecycle management practices, including source control, task management, CI/CD, automated testing, release management, and DevOps practices.
• Experience working with ERP systems, financial systems, enterprise platforms, or complex business applications preferred.
• Experience with SQL, relational databases, APIs, data integration, application interfaces, or similar toolsets for analyzing and implementing business rules and data-driven solutions.
• Experience working in a complex, service-intensive, deadline-driven enterprise environment.
• Hospitality, timeshare, finance, accounting, or enterprise business solutions experience preferred., * Solid understanding of AI application development patterns, including LLMs, prompt design, grounding, retrieval-augmented generation, agentic workflows, and AI-assisted automation.
• Familiarity with Model Context Protocol concepts, AI tool integration, function calling, enterprise connectors, and secure system-to-system interactions.
• Proficient in object-oriented programming, with the ability to design application components that are maintainable, scalable, secure, and testable.
• Proficiency with modern software engineering practices, including API design, integration patterns, source control, code reviews, automated testing, CI/CD, and production support.
• Preferred technical experience with.NET/C#, Java, and/or Python.
• Knowledge of cloud-based AI and application services, preferably Microsoft Azure AI services, Azure OpenAI, Azure AI Search, Microsoft Fabric, or comparable platforms.
• Knowledge of ERP systems and enterprise business processes; financial systems experience preferred.
• Solid in SQL and data analysis skills with the ability to understand data structures, business rules, data quality issues, and integration requirements.
• Ability to evaluate AI solution quality, including accuracy, reliability, explainability, performance, cost, security, and operational supportability.
• Understanding of responsible AI principles, data privacy, security, role-based access, auditability, and governance requirements.
• Demonstrated ability to learn complex business processes and develop technology solutions that address business needs in a holistic and sustainable manner.
• Ability to work effectively with business stakeholders, software engineers, architects, data teams, security teams, and external service providers.
• Strong communication skills with the ability to explain AI concepts, technical designs, risks, and tradeoffs to both technical and non-technical audiences.
• Solid analytical, problem-solving, troubleshooting, and critical-thinking skills.
• Proactive, motivated, disciplined, and comfortable working independently in a fast-paced, evolving technology environment.
• Effective at prioritizing work, managing ambiguity, and following through on commitments.
• Demonstrated agility in a constantly changing, deadline-oriented environment.
• Customer-focused approach with a commitment to delivering secure, reliable, well-engineered solutions that create business value.
• Ability to provide technical support and guidance to teams adopting AI-enabled development practices.