AI Engineer - REMOTE USA

Acliviti Consulting Group, LLC•Chicago, IL

11h•Remote

About The Position

We are seeking a Senior AI Implementation Engineer to build and deploy AI-powered customer experience solutions for enterprise clients. This is a hands-on engineering role focused on development, configuration, integration, testing, and deployment of conversational AI and automation solutions. You will take business and technical requirements and turn them into production-ready solutions using platforms such as Cognigy, and other conversational AI technologies. You will work with LLMs, AI agents, APIs, enterprise applications, and cloud technologies to build solutions that are reliable, scalable, and deliver measurable customer outcomes. You will work closely with Project Managers, Architects, Engineers, and clients throughout the implementation lifecycle, from development through UAT, go-live, and optimization.

Requirements

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 contact center concepts such as 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.

Nice To Haves

Hands-on implementation experience with Cognigy, PolyAI, or similar platforms.
Experience integrating conversational AI with NICE CXone, Genesys Cloud, or similar CCaaS platforms.
Experience with SIP-based voice integrations and telephony troubleshooting.
Experience with RAG, knowledge retrieval, and enterprise knowledge integrations.
Experience implementing agentic AI workflows and tool-based automation.
Experience with Salesforce, ServiceNow, or similar enterprise platforms.
Experience with Python or TypeScript.
Experience with AWS, Azure, or GCP.
Experience with Git/GitHub, CI/CD practices, and development lifecycle management.
Experience delivering solutions within a consulting or professional services environment.

Responsibilities

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 within conversational AI platforms.
Implement AI agents and agentic workflows to automate customer interactions and business processes.
Configure knowledge retrieval and RAG capabilities where appropriate.
Implement AI guardrails, fallback logic, validation, error handling, and escalation paths.
Develop and optimize conversational experiences based on testing, performance, and customer feedback.
Translate business requirements and functional designs into working, production-ready solutions.
Configure context management, session variables, and data handling throughout conversational interactions.
Integrate conversational AI platforms with enterprise contact center solutions such as NICE CXone, Genesys Cloud, and similar CCaaS platforms.
Configure and troubleshoot voice integrations, call routing, transfers, and escalation to live agents.
Implement and support telephony integrations using SIP, APIs, webhooks, or platform-native connectors.
Configure AI-to-agent handoffs, including transferring conversation context, collected data, and customer information.
Work with IVR, ACD, skills, queues, and routing configurations to support AI-driven customer experiences.
Troubleshoot issues across conversational AI platforms, telephony infrastructure, and contact center integrations.
Collaborate with CCaaS engineers and architects to ensure AI solutions align with existing contact center environments.
Develop conversational logic, integrations, API orchestration, and data transformations.
Build and consume REST APIs.
Work with JSON, webhooks, and event-driven integrations.
Integrate AI solutions with CRM, ERP, databases, knowledge bases, and other enterprise applications.
Configure and troubleshoot authentication methods, including OAuth, API keys, and tokens.
Develop and troubleshoot JavaScript-based logic and custom integrations.
Utilize Python or TypeScript where appropriate for platform-specific development.
Use Git/GitHub and established development practices for version control and collaboration.
Troubleshoot technical issues across applications, integrations, and AI platforms.
Develop and execute test cases for conversational AI and integrated solutions.
Perform functional, integration, regression, and performance testing.
Validate AI responses, conversational flows, business logic, integrations, and system behavior.
Test conversational experiences across voice and digital channels, including error handling and escalation scenarios.
Troubleshoot defects, analyze logs, and identify root causes.
Support client UAT and resolve issues through production readiness.
Support deployments, go-live activities, and post-production stabilization.
Monitor solution performance and implement improvements based on production behavior and customer feedback.
Create and maintain technical documentation, integration details, configuration documentation, and support runbooks.
Work directly with clients, architects, project managers, and internal technical teams to understand implementation requirements.
Participate in technical discovery sessions, solution reviews, and implementation discussions.
Identify technical dependencies, risks, and integration requirements early in the project lifecycle.
Communicate technical issues, troubleshooting findings, and recommendations clearly.
Provide technical support for demos, prototypes, and proof-of-concepts.
Take ownership of assigned implementation activities and deliverables.
Contribute to reusable components, implementation templates, development standards, and best practices.
Stay current on conversational AI technologies, agentic AI capabilities, and CCaaS platform advancements.