Artificial Intelligence Engineer

Location: Remote, Canada

Role Type: Permanent Full-Time

Company Overview

Join Connex, a leading technology solutions provider with over 600 professionals across 14 offices throughout North America. We help organizations accelerate digital transformation through innovative cloud, AI, automation, and customer experience technologies. Our teams work at the forefront of emerging technologies, delivering intelligent solutions that improve customer engagement, operational efficiency, and business performance.

At Connex, we foster a culture of innovation, collaboration, accountability, and continuous learning, empowering our employees to solve complex business challenges using modern technologies and AI-driven solutions.

Position Overview

We are seeking an experienced AI Engineer with expertise in Google Contact Center AI (CCAI) and Google Cloud Platform (GCP) to design, develop, implement, and optimize next-generation AI-powered customer experience solutions.

The successful candidate will play a key role in building intelligent virtual agents, conversational AI solutions, speech analytics capabilities, and customer service automation platforms that enhance customer experiences across contact center environments. This role requires strong technical expertise in conversational AI, large language models (LLMs), cloud-native architectures, integrations, and contact center technologies.

Experience with Google Customer Engagement Suite (GCEX) is highly desirable, though not mandatory.

The ideal candidate is both technically hands-on and customer-focused, with the ability to collaborate across business, operations, architecture, engineering, and contact center teams to deliver scalable and impactful AI solutions.

Key Responsibilities

Conversational AI Solution Development (35%)

- Design, develop, and deploy conversational AI solutions using Google Contact Center AI (CCAI) technologies.
- Build and optimize virtual agents, voice bots, chatbots, conversational workflows, and self-service experiences.
- Develop integrations between conversational platforms, enterprise applications, CRM systems, knowledge bases, and backend services.
- Design conversation flows, intents, entities, prompts, and dialogue management strategies.
- Improve customer interactions through natural language understanding (NLU) and generative AI capabilities.
- Support AI solution testing, tuning, optimization, and production deployment activities.

Cloud Architecture & Engineering (25%)

- Design and implement scalable AI and customer experience solutions on Google Cloud Platform (GCP).
- Develop cloud-native services leveraging Google AI, Vertex AI, Dialogflow CX, Cloud Functions, Cloud Run, Pub/Sub, BigQuery, and related services.
- Build APIs, microservices, and integration layers to connect AI solutions with enterprise platforms.
- Participate in architecture reviews and contribute to platform design decisions.
- Ensure solution scalability, reliability, security, and performance.
- Support CI/CD pipelines, infrastructure automation, and DevOps practices where applicable.

AI, LLM & Automation Innovation (15%)

- Design and implement Generative AI and LLM-driven customer service use cases.
- Evaluate emerging AI technologies and identify opportunities to enhance the customer experience.




- Implement prompt engineering, retrieval-augmented generation (RAG), knowledge search, and AI orchestration capabilities.
- Collaborate with business stakeholders to identify high-value automation opportunities.
- Leverage AI to improve agent productivity, customer self-service, case resolution, and operational efficiency.

Analytics, Monitoring & Optimization (15%)

- Monitor conversational AI performance and customer interaction outcomes.
- Analyze customer conversations, containment rates, escalations, intent accuracy, and engagement metrics.
- Develop dashboards, reporting, and performance monitoring solutions.
- Identify trends and optimization opportunities to continuously improve AI effectiveness.
- Support model tuning and refinement based on business outcomes and customer feedback.

Stakeholder Collaboration & Solution Delivery (10%)

- Collaborate with business stakeholders, contact center leaders, architects, product owners, and technology teams.
- Participate in Agile ceremonies, planning sessions, solution workshops, and design reviews.
- Translate business requirements into technical designs and scalable AI solutions.
- Provide technical leadership and guidance on AI best practices and industry trends.
- Support documentation, knowledge transfer, and operational readiness activities.

Qualifications

- 5+ years of experience in Software Engineering, AI Engineering, Machine Learning Engineering, Cloud Engineering, or related technical roles.
- 3+ years of hands-on experience working with Google Cloud Platform (GCP).
- Experience implementing Google Contact Center AI (CCAI), Dialogflow CX, or comparable conversational AI platforms.
- Strong experience designing and developing cloud-native applications and microservices.
- Experience building APIs, integrations, and enterprise-scale solutions.
- Strong understanding of NLP, conversational AI, chatbots, virtual agents, and speech technologies.
- Experience working with Generative AI, LLMs, prompt engineering, and AI automation solutions.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management capabilities.
- Experience working within Agile delivery environments.
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, or a related discipline (or equivalent practical experience).

Mandatory Skills

Google Contact Center AI (CCAI)

- Hands-on experience implementing and supporting Google Contact Center AI solutions.
- Strong knowledge of Dialogflow CX, conversational design, intent modeling, entity management, and virtual agent development.
- Experience integrating conversational AI solutions into contact center environments.
- Understanding of voice AI, speech-to-text, text-to-speech, and conversational automation technologies.
- Experience optimizing chatbot and virtual agent performance.

Google Cloud Platform (GCP)





- Strong experience designing and deploying solutions on Google Cloud Platform.
- Experience with services such as Vertex AI, BigQuery, Cloud Functions, Cloud Run, Pub/Sub, Cloud Storage, and API Gateway.
- Experience developing cloud-native applications and scalable architectures.
- Knowledge of cloud security, IAM, networking, monitoring, and operational best practices.

Software Engineering & Integration

- Strong programming experience in Python, Java, JavaScript, or related languages.
- Experience building REST APIs, microservices, and event-driven architectures.
- Experience integrating AI platforms with CRM, contact center, business applications, and enterprise systems.
- Familiarity with version control, CI/CD pipelines, and DevOps practices.

AI & Machine Learning

- Experience working with Generative AI technologies and large language models (LLMs).
- Knowledge of prompt engineering, retrieval-augmented generation (RAG), vector search, and AI orchestration frameworks.
- Understanding of NLP, intent classification, entity extraction, and conversational analytics.
- Ability to evaluate AI performance metrics and optimize outcomes.

Desirable Skills

- Experience with Google Customer Engagement Suite (GCEX).
- Experience with Genesys Cloud CX, NICE CXone, Five9, Amazon Connect, Cisco Contact Center, or similar contact center technologies.
- Experience implementing agent assist, knowledge assist, call summarization, sentiment analysis, or speech analytics solutions.
- Experience with Vertex AI Agent Builder and Google AI services.
- Familiarity with LangChain, LangGraph, OpenAI, Anthropic, Gemini, or other enterprise AI ecosystems.
- Experience with data engineering, ETL pipelines, and analytics platforms.
- Experience with Kubernetes, Docker, Terraform, or Infrastructure as Code (IaC).
- Experience building AI governance, monitoring, and responsible AI controls.
- Experience within Financial Services, Telecommunications, Healthcare, Insurance, Retail, or other large enterprise environments.
- Google Cloud Professional Cloud Architect, Qualified Machine Learning Engineer, or related certifications.

What Success Looks Like The successful candidate will deliver scalable and innovative AI-powered customer experience solutions that improve customer satisfaction, increase automation rates, and reduce operational effort. They will effectively bridge business requirements and technical implementation, drive adoption of AI technologies across contact center operations, and continuously identify opportunities to leverage conversational AI, generative AI, and cloud technologies to create measurable business value.

Why Connex?

- Opportunity to work on enterprise-scale AI, customer experience, and digital transformation initiatives.
- Exposure to cutting-edge Google AI, CCAI, Vertex AI, and Generative AI technologies.
- Hybrid work environment based in Toronto with access to large-scale enterprise clients and programs.
- Collaborate with highly skilled cloud, AI, customer experience, and engineering professionals.
- Participate in innovative projects shaping the future of customer engagement and intelligent automation.
- Join a collaborative culture that values innovation, accountability, professional growth, and continuous learning.

📌 Artificial Intelligence Engineer (Canada)
🏢 Connex Telecommunications
📍 Canada