AI Engineer

ACLIVITI

. Build, configure, and deploy conversational AI solutions across voice and digital channels .

Posted 10/9/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying conversational AI solutions, integrating with enterprise applications, and implementing complex workflows. Proficient in technical troubleshooting, API orchestration, and client collaboration to ensure successful project delivery.

Highest-signal resume keywords

Conversational AI ImplementationJavaScript DevelopmentAPI IntegrationTechnical TroubleshootingClient-Facing Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringConversational Flows DevelopmentREST APIsPrompt EngineeringData TransformationsTesting and DebuggingAI Agent WorkflowsIntegration with Telephony PlatformsConfiguration DocumentationEnterprise Integrations

Soft Skills

Problem-SolvingStrong CommunicationClient Collaboration

Tools & Technologies

CognigyPolyAINICE CXoneGenesys CloudGit/GitHubAWSAzureGCPSalesforceServiceNow

Industry Keywords

Conversational AIVirtual AgentsChatbotsVoicebotsIVRACDCCaaSRAGAgentic AIProfessional Services

Tech Stack

Tools & technologies

AWSAzureCloudERPGoogle Cloud PlatformJavaScriptPythonServiceNowTypeScript

About the role

Key responsibilities & impact

Build, configure, and deploy conversational AI solutions across voice and digital channels
Develop conversational flows, bot logic, intents, entities, business rules, prompts, and AI agent workflows
Configure and integrate LLM-powered capabilities, knowledge retrieval, and RAG
Implement AI agents, guardrails, fallback logic, validation, error handling, and escalation paths
Integrate conversational AI platforms with CCaaS and telephony platforms such as NICE CXone and Genesys Cloud
Configure voice integrations, call routing, transfers, IVR, ACD, skills, queues, and live-agent handoffs
Develop conversational logic, API orchestration, data transformations, REST APIs, webhooks, and custom integrations
Integrate solutions with CRM, ERP, databases, knowledge bases, and other enterprise applications
Use JavaScript, Python, or TypeScript and Git/GitHub for development and collaboration
Develop and execute functional, integration, regression, and performance tests
Troubleshoot defects, analyze logs, identify root causes, and resolve technical issues
Support client UAT, deployments, go-live activities, post-production stabilization, and performance monitoring
Create and maintain technical documentation, configuration documentation, integration details, and support runbooks
Collaborate with clients, architects, project managers, CCaaS engineers, and internal technical teams
Participate in discovery sessions, solution reviews, demos, prototypes, and proof-of-concepts
Identify dependencies and risks, own implementation deliverables, and contribute reusable components and development standards

Requirements

What you’ll need

5+ years of experience in software engineering, technical implementation, enterprise integrations, or professional services
Hands-on experience implementing conversational AI, virtual agents, chatbots, voicebots, or AI-powered applications
Experience with conversational AI platforms such as Cognigy, PolyAI, Google CCAI, Amazon Lex, or similar technologies
Strong JavaScript skills, including working with APIs, JSON, variables, and custom logic
Experience integrating enterprise applications using REST APIs, webhooks, and authentication mechanisms
Experience with LLMs, prompt engineering, and AI-powered conversational workflows
Experience integrating solutions with enterprise contact center or telephony environments
Understanding of IVR, ACD, call routing, skills, queues, and agent transfers
Experience with technical troubleshooting, testing, debugging, and production deployments
Ability to independently investigate and resolve technical issues across multiple platforms
Strong communication, problem-solving, and client-facing collaboration skills
Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
Preferred: Cognigy, PolyAI, NICE CXone, Genesys Cloud, SIP, RAG, agentic AI, Salesforce, ServiceNow, Python, TypeScript, AWS, Azure, GCP, Git/GitHub, CI/CD, and consulting or professional services experience
Authorization to work in the United States
Availability to work as a 1099 contractor is requested

Benefits

Comp & perks

Remote-first work environment
Full-time employment
Opportunity to work on emerging conversational AI and agentic AI technologies
Exposure to enterprise customer experience transformation projects
Collaboration with cross-functional teams and enterprise clients