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Requirements and responsibilities
Role: Senior Principal, AI Software Engineer– Agentic & Industry SolutionsLocation- TX (Remote)Role Type: FulltimeBe the one building AI-powered experiences where they matter most.Senior Principal, AI Software Engineer– Agentic & Industry SolutionsQualifications:Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or related discipline; Master's degree preferred10+ years of experience in software engineering, solution architecture, enterprise integration, or cloud-native application development5+ years of experience designing and implementing AI, Conversational AI, automation, or workflow orchestration solutionsStrong hands-on development experience building scalable enterprise applicationsProven ability to move solutions from concept and prototype through production deploymentDemonstrated technical leadership skills and ability to mentor engineers and architectsStrong communication and stakeholder engagement skills with ability to collaborate across Product, Engineering, and Strategic Customer teamsExperience building Agentic AI platforms, copilots, virtual agents, digital assistants, or intelligent automation solutionsExperience creating reusable solution accelerators, frameworks, and industry-specific assetsUnderstanding of industry processes within Financial Services, Healthcare, Insurance, Retail, Telecommunications, or Public Sector is a plusContributions to technical communities, open-source projects, patents, or innovation initiatives is a plusCandidates must have willingness to travel as necessary; a valid passport is requiredTechnical proficiency in the following is not necessary, but a plus:Genesys Cloud Architecture, AI Studio, Copilot, Architect, Journey Management, Experience Orchestration, APIs and Event FrameworksMulti-Agent Systems, AI Skills and Agent Development, LLM Integration, RAG Architectures, Knowledge Systems, AI Workflow AutomationAI Frameworks such as LangGraph, CrewAI, Semantic Kernel, LangChain, AutoGen, OpenAI APIs, Anthropic APIs, AWS BedrockPython, JavaScript/TypeScript, REST APIs, Event-Driven Architectures, Microservices, Cloud platforms (AWS, Azure, Google Cloud)Expertise with RAG architectures, vector databases, knowledge orchestration, and enterprise search solutionsExperience integrating AI solutions with CRM, ERP, Service Management, and enterprise workflow platformsPurpose:The Principal Architect and AI Engineer – Agentic & Industry Solutions is a highly technical, hands-on leader responsible for designing, building, and scaling transformative AI-powered solutions on Genesys Cloud. Working within the Innovation Solutions organization, this role drives the development of reusable Agentic AI capabilities, industry-specific solution accelerators, and intelligent workflow automation that enable organizations to fundamentally transform customer and employee experiences. The Principal Architect and AI Engineer provides technical leadership and expertise across architecture, development, and solution delivery, collaborating with Product, Engineering, Strategic Customers, Industry SMEs, and Technology Partners to convert emerging AI technologies into scalable, market-leading solutions.Benefits:Medical, Dental, and Vision Insurance.Telehealth coverageFlexible work schedules and work from home opportunitiesDevelopment and career growth opportunitiesOpen Time Off in addition to 10 paid holidays401(k) matching programAdoption AssistanceFertility treatmentsPre-Screening QuestionsQ1: Have you personally designed and deployed an AI or conversational orchestration solution that currently handles production traffic in a live enterprise environment?Q2: ave you built applications using advanced multi-agent or orchestration frameworks like LangGraph, CrewAI, or Semantic Kernel?Q3: In your previous roles, have you developed reusable solution accelerators, modular frameworks, or technical assets designed to be shared across multiple engineering teams or industry verticals?Q4: Do your technical designs frequently incorporate advanced RAG patterns, vector databases, or enterprise knowledge graphs integrated with systems like CRMs or ERPs?
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