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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and delivering production-ready conversational AI agents, with a strong focus on developing scalable systems for various industries. Proficient in integrating AI agent evaluation frameworks and collaborating with stakeholders to drive alignment and solve complex challenges.
Highest-signal resume keywords
AI Agent Lifecycle ManagementEnd-to-End Production SystemsAI/LLM-Powered Systems DevelopmentReact, TypeScript, or Go FamiliarityTechnical Problem-Solving
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Conversational AI DevelopmentAI Agent Evaluation FrameworksOrchestration ToolingRAG PipelinesPrompt Engineering
Soft Skills
Clear CommunicationCustomer-Facing ExperienceProblem-SolvingAdaptabilityCollaboration
Industry Keywords
Financial ServicesHealthcareCommerceCustomer ExperienceGenerative Development Workflows
Tech Stack
Tools & technologiesReactTypeScriptGo
About the role
Key responsibilities & impact- Architect and deliver production-ready conversational AI agents
- Build live, scalable agentic AI systems for financial services, healthcare, commerce, and other sectors
- Own the AI agent lifecycle from pilot through launch and ongoing refinement
- Collaborate with enterprise decision-makers to solve high-priority challenges with agentic AI
- Feed field patterns and problems into platform, tooling, and product roadmap evolution
- Develop agents that outperform human operators in areas such as retention and churn reduction
- Build agents for nuanced, integrated customer interactions across CX use cases
- Design reusable agent frameworks for different industries
- Drive design partnerships for agent architectures, self-service features, and generative development workflows
- Integrate emerging voice models into enterprise-grade deployments
- Establish standards for constructing, evaluating, and improving AI agents in production
Requirements
What you’ll need- Hands-on experience building and operating end-to-end production systems at scale
- Natural builder's mentality with high personal agency
- Startup founder or early engineer experience is highly valued
- Proven technical problem-solving ability in rapidly shifting, loosely defined environments
- Experience developing or operating AI/LLM-powered systems in production is a major plus
- Working knowledge of AI agent evaluation frameworks, orchestration tooling, RAG pipelines, and prompt engineering
- Familiarity with React, TypeScript, and/or Go is an advantage
- Comfortable working face-to-face with customers to unpack problems and deliver practical solutions
- Prior customer-facing or externally-led technical experience is a plus
- Clear, direct communication with engineers and executives
- Comfortable operating in ambiguity and making forward progress without complete clarity
- Able to balance competing priorities and drive alignment across technical and business teams
Benefits
Comp & perks- Build AI agents that run in production at meaningful scale
- Work shoulder-to-shoulder with leaders at globally recognized enterprises and high growth startups
- Directly influence the direction of NiCE's AI agent platform
- Genuine autonomy and end-to-end ownership across the agent lifecycle
- Access to the latest AI models, infrastructure, and research