This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves shaping the future of voice and multimodal interfaces within an innovative team. Your efforts will directly impact user experiences through the design of AI-based conversational interactions. - Lead design vision and execution for AI-based conversational and multimodal experiences, advocating usability and user-centered design principles. - Develop and promote conversation design best practice standards, reusable interactional patterns, and processes. - Deliver effective design documentation to communicate experience requirements, design principles, best practices, prototypes, and multimodal flows. - Identify opportunities for usability testing and research efforts by creating prototypes and participating in evaluation sessions. - Build strong relationships with internal stakeholders to ensure a connected end-to-end user experience. - Monitor industry trends and drivers of customer satisfaction. - Visualize experiences using storyboards, customer journeys, user flows, and prototypes to illustrate vision. - Balance user needs, technical constraints, and product objectives to craft world-class multimodal user experiences. Qualifications - 5+ years creating conversational design experiences. - Ability to combine vision with strong creative design execution. - Strong portfolio showcasing expertise, craft, aesthetics, and depth of thought. - Experience designing for Generative or Agentive AI-powered experiences. - Understanding of machine learning & natural language processing (NLP) fundamentals. - Experience incorporating research into the design process. - Ability to work independently, be organized, self-motivated, and attentive to detail. - Excellent written, visual, and verbal communication skills. - Proficient in common design tools (e.g., Figma, VoiceFlow, ProtoPie, etc.). - Demonstrated experience documenting for voice-only, voice-forward, and multimodal experiences. - Experience creating interactive prototypes for multimodal experiences (voice, sound, visuals, touch, chat, etc.). - Familiarity with platforms such as Salesforce Service Cloud, Einstein Bots, Prompt Builder, and Google Vertex AI. Benefits - Competitive salary range between $106,000 - $163,000 based on qualifications. - Bonus potential based on company performance and individual contributions. - Comprehensive health benefits including medical, dental, and vision coverage. - Flexible Spending Accounts and Health Savings Account options. - Retirement savings plan to help secure your financial future. - Paid vacation and holidays to recharge and maintain work-life balance. - Tuition assistance programs to support ongoing education and growth. - Employee assistance program for personal and professional support. - GM vehicle discounts and various other perks.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves shaping the future of voice and multimodal interfaces within an innovative team. Your efforts will directly impact user experiences through the design of AI-based conversational interactions. - Lead design vision and execution for AI-based conversational and multimodal experiences, advocating usability and user-centered design principles. - Develop and promote conversation design best practice standards, reusable interactional patterns, and processes. - Deliver effective design documentation to communicate experience requirements, design principles, best practices, prototypes, and multimodal flows. - Identify opportunities for usability testing and research efforts by creating prototypes and participating in evaluation sessions. - Build strong relationships with internal stakeholders to ensure a connected end-to-end user experience. - Monitor industry trends and drivers of customer satisfaction. - Visualize experiences using storyboards, customer journeys, user flows, and prototypes to illustrate vision. - Balance user needs, technical constraints, and product objectives to craft world-class multimodal user experiences. Qualifications - 5+ years creating conversational design experiences. - Ability to combine vision with strong creative design execution. - Strong portfolio showcasing expertise, craft, aesthetics, and depth of thought. - Experience designing for Generative or Agentive AI-powered experiences. - Understanding of machine learning & natural language processing (NLP) fundamentals. - Experience incorporating research into the design process. - Ability to work independently, be organized, self-motivated, and attentive to detail. - Excellent written, visual, and verbal communication skills. - Proficient in common design tools (e.g., Figma, VoiceFlow, ProtoPie, etc.). - Demonstrated experience documenting for voice-only, voice-forward, and multimodal experiences. - Experience creating interactive prototypes for multimodal experiences (voice, sound, visuals, touch, chat, etc.). - Familiarity with platforms such as Salesforce Service Cloud, Einstein Bots, Prompt Builder, and Google Vertex AI. Benefits - Competitive salary range between $106,000 - $163,000 based on qualifications. - Bonus potential based on company performance and individual contributions. - Comprehensive health benefits including medical, dental, and vision coverage. - Flexible Spending Accounts and Health Savings Account options. - Retirement savings plan to help secure your financial future. - Paid vacation and holidays to recharge and maintain work-life balance. - Tuition assistance programs to support ongoing education and growth. - Employee assistance program for personal and professional support. - GM vehicle discounts and various other perks.

• Design and build AI-powered features for VSTAR and other EDI platforms, including intelligent tutoring capabilities, semantic search, content recommendations, and LLM-based tools for learners and educators • Apply appropriate AI implementation patterns and strategies such as RAG architectures, agentic workflows, prompt engineering strategies, and LLM orchestration patterns appropriate to educational use cases • Develop backend services and APIs that expose AI capabilities for integration into VSTAR and other applications, working with the development team to determine appropriate integration patterns • Evaluate vender versus open-source AI products and services based on performance, cost, and reliability considerations • Ensure responsible AI practices, including appropriate guardrails, content filtering, and transparency in AI-assisted features • Build and maintain ML pipelines in Databricks for feature engineering, model training, and evaluation • Deploy models and AI services to production with appropriate monitoring, logging, and error handling • Implement MLOps practices proportionate to our maturity: version control, testing, documentation, and reproducibility • Ensure performance, reliability, and scalability of AI-powered services • Own the full lifecycle of deployed AI features, including maintenance, iteration, and retirement • Partner with data engineering to ensure AI systems integrate cleanly with our data infrastructure • Collaborate with software developers to integrate AI features into existing applications • Proactively communicate progress, challenges, and decisions to the team through regular check-ins, documentation, and asynchronous updates • Work with product and educational leadership to identify high-impact AI opportunities • Contribute to EDI's AI strategy and help establish best practices for responsible AI development in medical education • Maintain clear documentation and support knowledge sharing across the team • Stay current with developments in AI tooling, particularly as they apply to education and knowledge work

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking an experienced AI Application Developer with strong .NET and Azure AI expertise to support enterprise initiatives focused on modernizing operational systems through artificial intelligence. This role involves designing and implementing AI-powered enterprise applications that enhance digital services, automate workflows, and improve operational efficiency. - Build AI-enabled web applications using ASP.NET Core, Azure AI Services, and modern AI orchestration frameworks. - Integrate enterprise systems with large language models (LLMs) deployed in both cloud and local environments. - Collaborate closely with AI engineers, data scientists, DevOps teams, and enterprise application developers within an agile development environment. Qualifications - Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience. - 3+ years of experience developing applications using ASP.NET Core or ASP.NET MVC. - Strong development experience using C# and RESTful APIs. - Experience integrating applications with Azure AI services such as Azure OpenAI, Azure Cognitive Services, and Azure Cognitive Search. - Experience running or integrating locally hosted large language models using tools such as Ollama. - Hands-on experience with AI orchestration frameworks such as Semantic Kernel or AutoGen. - Strong knowledge of AI architecture patterns including Retrieval-Augmented Generation (RAG), vector search, and semantic search. - Experience with asynchronous programming and scalable service architectures. - Familiarity with Azure Blob Storage, Azure Functions, and Azure DevOps CI/CD pipelines. Requirements - Integrate enterprise applications with Azure AI services, including Azure OpenAI, Cognitive Services, and Cognitive Search. - Design hybrid AI architectures that support both cloud-hosted and locally deployed LLMs. - Implement Retrieval-Augmented Generation (RAG) pipelines to enable contextual AI responses. - Develop vector search and semantic search capabilities using embeddings and vector databases. - Build systems enabling contextual retrieval of enterprise knowledge and operational data. - Develop intelligent agent orchestration frameworks for complex AI workflows. - Implement multi-agent systems using frameworks such as Semantic Kernel or AutoGen. - Design automation systems capable of multi-step reasoning and task execution. - Implement Model Context Protocol (MCP) or similar interoperability frameworks for AI agents and enterprise services. - Create AI-driven automation to enhance operational processes and digital service delivery. - Optimize AI application performance, latency, and operational costs. - Manage hybrid inference environments including both cloud-based and locally hosted LLMs. - Develop scalable deployment strategies for enterprise AI systems. - Collaborate with DevOps teams to integrate AI workloads into CI/CD pipelines. - Participate in Agile development cycles, typically operating in three-week sprint iterations. - Provide weekly development updates and technical documentation. - Communicate project progress, risks, and blockers to technical leadership. - Deliver production-ready code and maintain documentation for enterprise AI solutions. Benefits - Experience building AI copilots or enterprise virtual assistants. - Development of LLM-powered chat interfaces and conversational AI solutions. - Experience building multi-agent AI systems. - Knowledge of embedding generation and vector indexing techniques. - Experience implementing hybrid retrieval strategies for enterprise data. - Familiarity with Model Context Protocol (MCP) or similar interoperability frameworks. - Experience with LangChain or ML.NET frameworks. - Experience implementing OpenAI function calling or tool integration frameworks. - Experience deploying AI models in both cloud and local inference environments. - Experience working in enterprise or government technology environments. - Familiarity with WCAG accessibility standards.