CCaaS GECX AI Engineer - Integration & Dev

Tata Consultancy Services

Phoenix (AZ)

On-site

USD 100,000 - 150,000

Full time

2 days ago
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Benefits offered by this job

Discretionary Annual Incentive
Medical Coverage
Family Leave
401K Plan
Training & Certification Reimbursement
Vacation & Holidays

Job summary

Tata Consultancy Services is seeking an experienced GECX AI Development & Integration Engineer to build and deploy contact center AI solutions on Google Cloud, with a focus on Five9 and Genesys Cloud CX integrations. The role requires hands-on experience in CCaaS, IVR, NLP, and API ecosystems.

You will design scalable architectures, collaborate with data scientists, and drive production deployments using modern AI tools and cloud platforms.

Qualifications

  • 5+ years of commercial software development experience.
  • Design and implement scalable CCaaS and IVA solutions leveraging leading Cloud and enterprise conversational AI / customer service solutions.
  • Specialization in Five9 and Genesys Cloud CX integrations.
  • Experience with API integrations and modern integration frameworks.

Responsibilities

  • Collaborate with product owners and engineers to translate complex requirements into deployment pipelines.
  • Design and implement CCaaS/IVA solutions on cloud platforms, including AI/ML components.
  • Develop integrations with CRMs/ERPs and external systems via APIs.
  • Lead rapid prototyping, PoCs, and production deployments.

Skills

CCaaS
GECX AI
Five9
Genesys Cloud CX
Python
Node.js
Java
REST APIs
JSON
CI/CD
DevOps
Kafka
SQL
NoSQL
DialogFlow CX
Vertex AI

Tools

APIGEE
DialogFlow CX
Vertex AI
SCRAPI
JSON scripting
API Integrations

Job description

Tata Consultancy Services is seeking an experienced GECX AI Development & Integration Engineer to build and deploy contact center AI solutions on Google Cloud, with a focus on Five9 and Genesys Cloud CX integrations. The role requires hands-on experience in CCaaS, IVR, NLP, and API ecosystems.

You will design scalable architectures, collaborate with data scientists, and drive production deployments using modern AI tools and cloud platforms.

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