Sr. Principal AI Software Engineer

Qualifications

• Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or related discipline; Master's degree preferred
• 10+ years of experience in software engineering, solution architecture, enterprise integration, or cloud-native application development
• 5+ years of experience designing and implementing AI, Conversational AI, automation, or workflow orchestration solutions
• Strong hands-on development experience building scalable enterprise applications
• Demonstrated technical leadership skills and ability to mentor engineers and architects
• Proven ability to move solutions from concept and prototype through production deployment
• Strong communication and stakeholder engagement skills with ability to collaborate across Product, Engineering, and Strategic Customer teams
• Experience building Agentic AI platforms, copilots, virtual agents, digital assistants, or intelligent automation solutions
• Understanding of industry processes within Financial Services, Healthcare, Insurance, Retail, Telecommunications, or Public Sector is a plus
• Contributions to technical communities, open-source projects, patents, or innovation initiatives is a plus

Requirements

• Candidates must have willingness to travel as necessary; a valid passport is required
• Technical proficiency in the following is not necessary, but a plus: Genesys Cloud Architecture, AI Studio, Copilot, Architect, Journey Management, Experience Orchestration, APIs and Event Frameworks
• Multi-Agent Systems, AI Skills and Agent Development, LLM Integration, RAG Architectures, Knowledge Systems, AI Workflow Automation AI Frameworks such as LangGraph, CrewAI, Semantic Kernel, LangChain, AutoGen, OpenAI APIs, Anthropic APIs, AWS Bedrock Python, 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 solutions
• Experience integrating AI solutions with CRM, ERP, Service Management, and enterprise workflow platforms

Skills

• Technical proficiency in the following is not necessary, but a plus: Genesys Cloud Architecture, AI Studio, Copilot, Architect, Journey Management, Experience Orchestration, APIs and Event Frameworks
• Multi-Agent Systems, AI Skills and Agent Development, LLM Integration, RAG Architectures, Knowledge Systems, AI Workflow Automation AI Frameworks such as LangGraph, CrewAI, Semantic Kernel, LangChain, AutoGen, OpenAI APIs, Anthropic APIs, AWS Bedrock Python, 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 solutions
• Experience integrating AI solutions with CRM, ERP, Service Management, and enterprise workflow platforms

Purpose

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.

Pre-Screening Questions

• Have you personally designed and deployed an AI or conversational orchestration solution that currently handles production traffic in a live enterprise environment?
• Have you built applications using advanced multi-agent or orchestration frameworks like LangGraph, CrewAI, or Semantic Kernel?
• 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?
• Do your technical designs frequently incorporate advanced RAG patterns, vector databases, or enterprise knowledge graphs integrated with systems like CRMs or ERPs?