Solutions Engineer (CCaaS)

Solutions Engineer (CCaaS)

Hybrid: 2 days in office

Contract Duration: 6 months with extension

Job Summary

We are seeking a highly skilled Solution Engineer to join our team and contribute with the design and implementation of Contact Centre as a Service (CCaaS) solutions. The ideal candidate will have subject matter expertise in architecting and deploying CCaaS solutions, with a strong focus on enhancing customer and agent experiences through innovative technology.

Key Responsibilities

• Participate in the design and architecture of CCaaS and other Contact Centre solutions, ensuring alignment with business objectives and technical requirements.
• Collaborate with cross-functional teams, including business lines, IT, and others, to gather requirements and develop comprehensive solution designs.
• Evaluate and select appropriate CCaaS platforms and technologies, such as Genesys Cloud, to meet the organization’s needs.
• Develop and maintain architectural documentation, including technical design documents, solution blueprints, and integration plans.
• Provide technical leadership and guidance to development teams during the implementation phase, ensuring adherence to architectural standards and best practices.
• Conduct regular reviews of the CCaaS solution to identify areas for improvement and optimization.
• Stay up-to-date with industry trends and emerging technologies in the CCaaS space, and recommend innovative solutions to enhance the customer and agent experience.
• Ensure the scalability, reliability, and security of the CCaaS solution, addressing any technical challenges that may arise.
• Implement AI tools in the Contact Centre: Act as a subject matter expert for the integration of AI technologies to enhance customer interactions and agent productivity, including natural language processing (NLP), machine learning, speech analytics, and AI-driven insights.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Proven experience as a Solution Engineer, with a focus on Contact Centre as a Service (CCaaS) solutions.
• Strong knowledge of CCaaS platforms and technologies, such as Genesys Cloud, and their integration with other enterprise systems.
• Excellent understanding of cloud computing principles and architectures.
• Experience with designing and implementing multi-channel and omnichannel contact center solutions.
• Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at all levels.
• Ability to work in a fast-paced, dynamic environment and manage multiple priorities.

Preferred Qualifications

• Experience with other CCaaS platforms, preferably Genesys or such as Amazon Connect or NICE inContact.
• Certification in relevant CCaaS technologies or cloud platforms.
• Knowledge of customer relationship management systems and their integration with CCaaS solutions.
• Experience with agile development methodologies and project management tools.

Additional AI Skills

• AI Integration: Experience in integrating AI technologies into CCaaS solutions to enhance customer interactions and agent productivity.
• Natural Language Processing (NLP): Proficiency in implementing NLP for automated customer service solutions, such as chatbots and virtual assistants.
• Machine Learning: Knowledge of machine learning techniques to analyze customer data and improve service delivery through predictive analytics.
• Speech Analytics: Experience with speech recognition and analytics to monitor and improve call quality and customer satisfaction.
• AI-Driven Insights: Ability to leverage AI to generate actionable insights from customer interactions and drive continuous improvement.
• Automation: Expertise in using AI for automating routine tasks and processes within the contact center to increase efficiency and reduce operational costs.
• Sentiment Analysis: Proficiency in using AI to analyze customer sentiment and tailor responses to improve customer experience.
• AI Ethics: Understanding of ethical considerations and best practices in deploying AI solutions in customer service environments.

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