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$20k – $86k per year (Estimated)
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In office (Pune)
Employment
Full-Time
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Capgemini is a French information technology services and consulting group founded in Grenoble in 1967 by Serge Kampf, and one of the largest IT service providers in the world. It designs, builds and runs systems for large enterprises and governments across some fifty countries, with a delivery workforce concentrated in India and a European client base heavier than most of its competitors. The group is organised into Capgemini Invent for strategy and design, Capgemini Engineering for research and development services acquired with Altran, and Sogeti for local technology services, and it has reoriented its portfolio around cloud migration, data platforms and generative AI.

AI Engineer - AI Voice Agent (Contact Center) ________________________________________ 1. Job Summary We are seeking a AI Engineer to design and implement AI-powered voice agent capabilities for contact center quoting workflows. This role focuses on building AI and backend services integrated with Cisco and GECX platforms for real-time customer interactions. 2. Key Responsibilities

  • Design and develop AI voice agent capabilities, including conversational logic and backend integrations
  • Drive implementation and integration across Cisco contact center and GECX (CX) platforms, along with AI-driven conversational components and Node.js services, enabling seamless end-to-end voice interaction flows
  • Build and maintain Node.js-based APIs and backend services supporting real-time voice interaction workflows
  • Implement and optimize prompt-based dialog flows, including conversation state and session management
  • Implement comprehensive dialogue flow logging, ensuring structured capturing of session states, prompt inputs, LLM responses, and latency metrics for downstream analytics, conversational auditing, and continuous prompt tuning.
  • Champion the integration of the Model Context Protocol (MCP) to standardize how the LLM voice agent securely accesses context, connects to internal enterprise data sources, and executes tools.
  • Develop the Python-based connector layer to bridge the real-time voice agent orchestration with backend applications, ensuring secure, auto-scaling, and ultra-low latency execution of serverless containerized AI workloads.
  • Collaborate with solution engineers and cross-functional teams to align on integration design and implementation approach
  • Troubleshoot and resolve production issues across AI, telephony integration, and backend layers
  • Contribute to performance tuning, scalability improvements, and system reliability
  • Mentor junior engineers and promote best practices in conversational AI and backend development 3. Required Skills & Qualifications
  • 8+ years of experience in software engineering, backend development, or AI-driven systems
  • Strong experience with Node.js backend development (APIs, microservices, integration layers)
  • Experience with system integration across distributed, real-time systems
  • Experience with AI-driven conversational platforms (voice/chat) and strong understanding of conversational design, including prompt-driven dialog flows and session/state management
  • Experience working with customer experience (CX) platforms (e.g., GECX) and integration with contact center systems
  • Deep experience with Cisco contact center platforms, along with strong understanding of telephony concepts such as SIP, call routing, and bot-to-agent handoffs
  • Strong problem-solving skills and ability to drive implementation independently within a defined architecture 4. Preferred / Nice-to-Have Skills
  • Experience contributing to end-to-end voice bot or conversational AI implementations
  • Familiarity with voice AI components, such as speech-to-text (ASR) and text-to-speech (TTS)
  • Exposure to contact center integrations (Cisco) and CX platforms (GECX)
  • Experience with microservices-based architectures and scalable backend systems
  • Awareness of modern conversational frameworks or MCP-like concepts
  • Experience in insurance or quoting workflows 5. Experience Requirements
  • 8+ years in software engineering / backend or integration roles
  • 2-4 years of experience in conversational systems, voice/chat platforms, or AI-driven interaction solutions
  • Proven experience working on multi-system integrations and real-time application flows

Requirements

GECX, GCP Cloud

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