AI INTEGRATION ENGINEER

Position Overview The AI Integration Engineer is responsible for designing, building, and continuously improving AI-powered integration solutions across the organization. Working within the integration team, this role is dedicated to AI initiatives: developing intelligent agents, improving tool calling and orchestration patterns, and evolving one-off AI implementations into standardized, reusable, evergreen solutions on the company's integration platform. This role bridges enterprise integration engineering and applied AI, ensuring data moving between customers, partners, and internal applications is enriched, transformed, and acted upon through modern inference-driven workflows. Knowledge Skills Required Integrity Adhere to Fracht's Core Values and Vision. Ability to operate in an open and honest manner and achieve a trusting and reliable relationship with team members, customers, and vendors. Ability to accept mistakes and learn from them without apportioning blame. Flexibility Learn and keep up to date with new developments in a rapidly evolving AI landscape. Work efficiently in an environment with multiple shifting priorities. Communication Effectively listen and communicate clearly with team members, customers, and vendors. Ability to interpret and disseminate information promptly, translating technical AI concepts for business stakeholders. Problem Solving Measure effectiveness in understanding problems and making timely practical decisions. Ability to work well in groups and/or individually to develop alternative solutions. Accountability Justify responsible actions and decisions to management. Be a reliable team player who can make accurate decisions with sense of urgency. Duties And Responsibilities Design, develop, and support AI-driven integration solutions on the company's integration platform (MuleSoft), from conceptualization through deployment and post-Go-Live support Build and maintain intelligent agents and agentic workflows, including tool calling, orchestration, memory, and guardrail patterns Evolve existing point solutions (e.g., direct LLM API connections) into standardized, reusable, evergreen frameworks that are plug-and-play rather than configuration-heavy Develop and maintain connections to LLM providers and model routing services; evaluate and recommend models for specific workloads Implement document and data extraction pipelines using AI inference, including validation, error handling, and reprocessing frameworks Design and implement retrieval patterns (RAG) to ground agents in company and client data, improving reliability and reducing hallucination Establish evaluation, observability, and monitoring practices for AI workflows to ensure production reliability, cost control, and measurable business value Stay current with the integration platform vendor's agentic offerings and emerging agentic frameworks; assess and adopt where they advance the AI roadmap Build reusable tools and services (e.g., MCP servers, standardized connectors) that can be shared across teams and agent implementations Collaborate with integration, Salesforce, and operational systems teams to embed AI capabilities into existing business processes Partner with business stakeholders and project leads to translate operational requirements into agent and integration designs Document solutions, patterns, and standards; contribute to the AI project portfolio and roadmap planning Maintain, support, and develop relational and non-relational databases as needed for AI workloads Other duties as assigned Education And/Or Work Experience Required Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent practical experience Minimum 3–5 years of software development experience, with hands-on experience in enterprise integration Demonstrated hands-on experience building LLM-powered applications or agents in production (tool calling, orchestration, prompt engineering, RAG) Experience with integration platforms (MuleSoft strongly preferred; IBM Sterling Integrator, Boomi, or similar considered) Familiarity with agentic frameworks and emerging agent orchestration and governance offerings in the enterprise integration ecosystem Experience working with LLM provider APIs (e.g., OpenAI, Anthropic, Google) and/or model routing platforms Experience developing REST APIs and real-time integrations with internal and external systems Knowledge of scripting/transformation languages (e.g., DataWeave, Python, JavaScript) Strong SQL scripting capabilities (T-SQL/DDL/DML) Experience with full software development lifecycle and CI/CD practices Minimum 2 years working in an Agile/Scrum environment Expertise in tools like JIRA/Confluence, SharePoint, and common program management tools Experience with monitoring and observability platforms preferred Industry experience within international supply chain, transportation, or logistics preferred Strong written and verbal skills, both business and technical Physical Requirements Ability to safely and successfully perform the essential job functions consistent with the ADA, FMLA and other federal, state, and local standards, including meeting qualitative and/or quantitative productivity standards. Ability to maintain regular, punctual attendance consistent with the ADA, FMLA and other federal, state, and local standards. Must be able to lift and carry up to 50 lbs. Prolonged periods of sitting at a desk and working on a computer. Must be able to talk, listen and speak clearly on telephone. Diversity and Inclusion We believe in creating an inclusive environment where everyone feels empowered and supported. We encourage individuals of all backgrounds, identities, and abilities to apply. We are committed to diversity and are proud to be an equal opportunity employer. Show more Show less