CCaaS Engineer

Job description

We Are: Accenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. With strong client relationships and deep industry expertise, we help our clients operate at the speed of life through the unlimited potential of imagination, technology and intelligence. Visit us at: www.accenture.com/song There will never be a typical day at Accenture Song, but that's why people love it here. The opportunities to make a difference while working on exciting client initiatives are limitless in this ever-changing space. You Are: A hands-on CCaaS Engineer with deep technical expertise in Amazon Connect and Google Cloud Contact Center AI (CCAI). You are passionate about building scalable, intelligent customer experience solutions that span both AWS and Google Cloud ecosystems. You thrive in fast-paced delivery environments, translate complex requirements into robust implementations, and work closely with architects, developers, and business stakeholders to deliver best-in-class contact center solutions. You are detail-oriented, a strong problem-solver, and committed to engineering excellence across both platforms. The Work: Designs, builds, configures, and maintains CCaaS solutions on Amazon Connect and Google CCAI across voice, chat, email, and messaging channels. Implements contact flows, IVR logic, routing strategies, and agent workspace configurations on both Amazon Connect and Google CCAI platform. Develops and integrates cloud-native services from AWS and Google Cloud to support end-to-end contact center workflows. Participates in legacy platform assessments and executes migration plans to Amazon Connect or Google CCAI as defined by solution architects. Builds and maintains CI/CD pipelines and infrastructure-as-code (IaC) across AWS and GCP environments. Implements and validates integrations between CCaaS platforms and enterprise systems such as CRM (Salesforce, MS Dynamics), WFM, and ticketing tools. Develops AI-powered features including virtual agents, chatbots, and agent assist capabilities leveraging Amazon Lex, Bedrock, Google Dialogflow CX, and CCAI Agent Assist. Supports testing, QA, and UAT cycles—writing test cases, executing regression tests, and resolving defects across the full solution stack. Monitors platform performance, troubleshoots production issues, and implements optimizations for reliability, latency, and cost efficiency on both platforms. Documents technical designs, configuration guides, runbooks, and deployment procedures for client and internal use. Contributes to Agile ceremonies—sprint planning, standups, retrospectives—and tracks delivery progress against milestones. Amazon Connect Engineering Configure Amazon Connect contact flows, routing profiles, queues, and agent hierarchies. Develop AWS Lambda functions and backend integrations in Python, Node.js, or Java. Build conversational AI experiences using Amazon Lex and integrate with Amazon Bedrock for GenAI-powered self-service. Implement real-time and historical analytics using Amazon Connect Contact Lens, Kinesis, and AWS reporting tools. Provision and manage AWS infrastructure (Lambda, DynamoDB, S3, Kinesis, API Gateway, CloudWatch) using Terraform or CloudFormation. Google CCAI Engineering Build and configure virtual agents using Dialogflow CX, including intent design, entity management, and conversation flow development. Implement CCAI Agent Assist to deliver real-time agent guidance, smart replies, and knowledge base surfacing. Develop CCAI Insights configurations for post-call analytics, topic modeling, and sentiment analysis. Integrate Google CCAI with telephony connectors and contact center platforms via CCAI Platform (CCAIP) or partner integrations. Leverage Google Cloud services (Cloud Functions, Pub/Sub, BigQuery, Vertex AI) to build supporting backend workflows and analytics pipelines. Provision GCP resources using Terraform or Google Cloud Deployment Manager. Migration & Integration Engineering Execute phased migration tasks from legacy contact center platforms to Amazon Connect or Google CCAI. Build and validate API-based integrations with CRM, WFM, and enterprise backend systems on both platforms. Support cutover planning, data migration, and rollback procedures to ensure business continuity. Conduct technical testing and performance benchmarking pre- and post-migration. AI & Automation Engineering Design and tune conversational AI flows across Amazon Lex / Bedrock and Google Dialogflow CX / Vertex AI. Implement agentic AI capabilities such as autonomous virtual agents and AI-assisted agent copilots on both platforms. Apply prompt engineering, RAG pipelines, and grounding techniques to optimize GenAI performance in CX contexts. Integrate CCAI Agent Assist and Amazon Q in Connect to deliver intelligent, real-time agent support. DevOps & Cloud Engineering Maintain IaC templates and automate provisioning across AWS (CloudFormation, CDK) and GCP (Terraform, Deployment Manager). Implement and manage CI/CD pipelines using AWS CodePipeline, Google Cloud Build, GitHub Actions, or Jenkins. Apply security best practices—IAM roles, encryption, VPC/VPN configurations—across AWS and GCP contact center environments. Monitor system health using CloudWatch and Google Cloud Operations Suite; set up alerting and participate in incident response. Basic Qualifications: 3+ years of hands-on engineering experience with Amazon Connect, Google CCAI, or both. Proven experience configuring and developing on Amazon Connect—including contact flows, Lambda integrations, Lex bots, and routing logic. Proven experience building and deploying Google Dialogflow CX virtual agents and integrating CCAI services (Agent Assist, Insights). Proficiency in at least one backend programming language: Python, Node.js, or Java. Working experience with AWS cloud services: Lambda, DynamoDB, S3, Kinesis, API Gateway, CloudWatch. Working experience with Google Cloud services: Cloud Functions, Pub/Sub, BigQuery, Cloud Storage, Google Cloud Operations Suite. Experience with CI/CD practices and IaC tools (Terraform, CloudFormation, CDK, or Cloud Deployment Manager). Familiarity with REST API design and integration patterns (microservices, event-driven architecture). Experience participating in Agile/Scrum delivery teams—sprint planning, backlog grooming, and daily standups. Strong understanding of security and compliance considerations in cloud contact center environments (PCI, PII, HIPAA). English is required for this position as this role will regularly interact with stakeholders across Canada, US and other countries across our Global footprint where English is the common language. Due to the significant high volume of interactions with these English-speaking stakeholders, which is inherent to this position, it is not possible to reorganize the company's activities to avoid this requirement. A minimum of a high school diploma or GED is required for this position. Nice to Have: AWS certification (e.g., AWS Certified Developer, AWS Certified Solutions Architect) and/or Google Cloud certification (e.g., Professional Cloud Developer, Professional Machine Learning Engineer). 5+ years of experience in contact center technology engineering or cloud application development. Experience with Amazon Q in Connect for real-time agent recommendations and knowledge retrieval. Experience with Google CCAI Platform (CCAIP) as a managed contact center solution. Hands-on experience with Vertex AI for fine-tuning or deploying generative AI models in CX workflows. Experience with CRM integrations such as Salesforce Service Cloud Voice, Microsoft Dynamics, or ServiceNow CTI on either platform. Experience with workforce management (WFM) platform