We are looking for a highly motivated Senior Applied AI Engineer to join our digital innovation team and help revolutionize how we serve our primarily B2C (Business-to-Consumer) customers. As a major appliance manufacturer, we’re committed to delivering seamless experiences for consumers across our contact center channels, including voice, chat, and messaging. This role is ideal for someone who is passionate about AI, automation, and customer service, with a hands-on approach to creating and optimizing use cases / agents for AI-driven interactions.

You’ll be responsible for designing, building and supporting scalable software solutions that power contact center operations and customer engagement. Working as an individual contributor within a cross-functional team of engineers, architects, and program leadership to deliver reliable, high-quality solutions and transactional capabilities, such as order management, scheduling repairs, processing warranty claims, and assisting with product troubleshooting. You will collaborate closely with senior architects on system design, partner with peer engineers on implementation and code quality, and provide guidance and mentorship to junior developers. You will contribute to technical decision-making, drive best practices in development and operations, and ensure solutions meet performance, security, and business requirements.
This position is headquartered in Louisville, KY with availability to work remotely.
Position
Senior Applied AI Engineer
Location
USA, Louisville, KY

How You'll Create Possibilities

AI Agent Development & Implementation

• Design, build, and maintain AI-driven conversational agents supporting customer engagement use cases, from FAQs to transactional workflows (e.g., order management, repair scheduling, troubleshooting)
• Develop and implement conversation flows, decision trees, and dialog management logic aligned to defined architectures and best practices
• Craft and optimize AI copilots and other employee-facing agents to drive efficiency and strengthen process adherence.
• Partner with architects, product owners, and domain experts to translate business requirements into scalable, maintainable AI solutions
• Contribute to the evolution of development standards, reusable components, and implementation patterns for AI agents

Agent Tuning & Optimization

• Configure, train, and tune AI/NLP models to improve intent recognition, entity extraction, and response quality
• Analyze agent performance metrics and interaction data to identify gaps and implement targeted improvements
• Support testing efforts, including user acceptance testing and iterative refinement based on real-world feedback

Transactional Flows & System Integration

• Implement and support transactional conversational flows that integrate with backend systems (e.g., CRM, ERP, telephony)
• Develop and maintain APIs and service integrations that enable AI agents to perform real-time actions and retrieve customer data
• Ensure solutions meet security, privacy, and compliance requirements when handling customer data and executing transactions

Cross-Functional Collaboration

• Collaborate with development peers, architects, and program management to deliver high-quality solutions within established timelines
• Work with operations and customer experience teams to understand pain points and support the delivery of AI-driven improvements
• Provide technical guidance and mentorship to junior engineers and contribute to team knowledge sharing

Operational Support & Continuous Improvement

• Monitor and troubleshoot production issues, ensuring reliability and performance of AI-driven systems
• Contribute to observability tracking of AI agent performance (e.g., containment, accuracy, customer satisfaction)
• Continuously improve code quality, test coverage, and deployment practices through CI/CD and DevOps standards
• Stay current with emerging AI, NLP, and contact center technologies and apply relevant advancements to ongoing work

What You'll Bring to Our Team

• Bachelor’s or Master’s degree in Computer Science, Engineering or a related field.
• 5 years of relevant software engineering experience, including at least 1 year working with AI use cases such as conversational AI or natural language processing in customer-facing solutions
• Proficiency with at least one cloud platform (e.g., AWS, Azure, GCP), particularly for event-driven and real-time architectures
• Hands-on experience with scripting languages (e.g., Python, JavaScript) to build integrations, enhance agent functionality, and support transactional workflows
• Proficiency in designing conversational flows, decision trees, and systems that support customer inquiries and transactions
• Experience integrating contact center platforms with CRM systems (e.g., Salesforce, Dynamics, ServiceNow), including screen pops, case workflows, and customer data synchronization
• Hands-on experience developing and optimizing AI chatbots or virtual assistants, including model training, conversation design, and performance improvement
• Strong problem-solving skills with the ability to design solutions that balance customer experience and business objectives
• Experience with CI/CD pipelines and DevOps practices, including automated testing and deployment
• Strong organizational skills with the ability to manage multiple priorities and deliverables
• Effective communication skills, with the ability to translate technical concepts for non-technical stakeholders
• Experience using work management tools such as Jira, Smartsheet, or similar to manage backlogs, track tasks/issues, coordinate dependencies, and communicate project status.

Preferred Qualifications:

• Experience working with a B2C contact center, especially in a consumer goods or appliance manufacturer environment.
• Hands-on experience integrating with Salesforce (e.g., Service Cloud, CTI adapters, APIs, event streams) to support agent workflows and customer data access
• Familiarity with telephony services such as Amazon Connect, Genesys, NICE, Five9, or similar platforms
• Knowledge of NLP models and how they can be fine-tuned for specific customer service applications.
• Background in customer journey mapping, process automation, or integrating AI with CRM systems (e.g., Salesforce).
• Passionate about continuous learning, especially in the AI/ML field, and driven by results.