GCP CES AI/ML Practice Architect- I

TEKsystems•Hanover, MD

2d•Remote

About The Position

As an organization, TEKsystems Global Services (TGS) provides a continuum of services ranging from Engagement Management to full functional Outsourcing including Offshore Centers in Canada and India. Our model provides the ability to engage customers beyond staffing when asked for more ownership, capabilities, or methodology while enhancing client/consultant support. We partner with progressive leaders to create opportunity, accelerate business transformation and help build the enterprises of tomorrow. We work with 80% of the Fortune 500 to address their technology, strategy, and talent needs. We innovate so industries stay ahead of what’s next. As a full stack technology and talent services provider, we partner with our customers across the globe to own change. Join us. At TEKsystems Global Services, we live in the tech world. We’re out in front of the trends and tools that shape industry and create fresh opportunities. All-in, fully engaged, high energy partnership is how we approach everything – our commitments and our people. Our people are at the center, fueling our high-performance and our inclusive culture. We’re doers, looking for doers who do the right thing. Roll-up your sleeves thought-leaders focused on creating possible. Team champions who declare success only when everyone achieves their ambitions. Sound like the career experience you’ve been searching for? We’re looking for a Practice Architect I – GCP CES to join our team. A practitioner who accelerates outcomes, affects positive change, and moves business forward. Let’s partner. Together, we can accomplish amazing things. Here’s what the opportunity supported through our TEKsystems Global Services (TGS) Talent Acquisition Team requires: Key Responsibilities Lead 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 Google CCAIP or Ujet 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: Lead 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.

Requirements

Bachelor's degree in Computer Science, Information Technology, or a related field.
Proven experience as a Solutions Architect, with a focus on Contact Centre as a Service (CCaaS) solutions.
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.

Nice To Haves

Experience with other CCaaS platforms, preferably Google CCAIP or such as Amazon Connect or NICE inContact.
Integrating the virtual agents with CcaaS environment - preferably DFCX
Knowledge of customer relationship management (CRM) systems, Workforce Management and their integration with CCaaS solutions.
Experience with Contact Center Reporting - knowledge of important KPI and Metrics
Experience with agile development methodologies and project management tools
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.
Google Cloud Professional Machine Learning Engineer
Google Cloud Professional Data Engineer

Responsibilities

Lead 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 Google CCAIP or Ujet 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.
Lead 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.