AI Solutions Architect - voice AI

Zingly; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Zingly in Bengaluru is seeking a hands-on Senior AI Engineer / AI Solutions Architect to design, develop, and deploy production-grade AI-powered customer engagement solutions across enterprise contact centers. You will lead building core AI capabilities, design scalable architectures, and integrate intelligent conversational solutions with CCaaS platforms.

Ideal candidates have experience delivering production-ready AI systems, with strong skills in STT/TTS, LLMs, RAG, tool calling, and

Qualifications

• Hands-on experience with enterprise CCaaS platforms or equivalent contact center infrastructure.

Responsibilities

• Design and develop AI-powered voice agents, conversational IVR systems, chatbots, and virtual assistants.
• Build real-time voice applications using STT, TTS, LLMs, and voice orchestration technologies.
• Develop omnichannel conversational solutions across voice, web chat, WhatsApp, SMS, and in-app messaging.
• Build LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and Agentic AI workflows.

Skills

Hands-on AI engineering

Real-time voice AI

System design

Python/Node.js/Java

Production-grade AI

Voice/chatbot development

Tools

LangChain

LangGraph

LlamaIndex

AWS

Azure

GCP

Job description

We are looking for a hands-on Senior AI Engineer / AI Solutions Architect to design, develop, and deploy production-grade AI-powered customer engagement solutions across enterprise contact center environments. The ideal candidate will have strong experience in Contact Center as a Service (CCaaS), real-time Voice AI, digital messaging, generative AI, and agentic AI. This role focuses on building core AI capabilities, designing scalable architectures, and integrating intelligent conversational solutions with enterprise contact center platforms. Candidates must have experience delivering production-ready solutions rather than working exclusively on prototypes or proofs-of-concept.

Responsibilities:

• Design and develop AI-powered voice agents, conversational IVR systems, chatbots, and virtual assistants.
• Build real-time voice applications using Speech-to-Text (STT), Text-to-Speech (TTS), LLMs, and voice orchestration technologies.
• Develop omnichannel conversational solutions across voice, web chat, WhatsApp Business, SMS, and in-app messaging.
• Build LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and Agentic AI workflows using frameworks such as LangChain, LangGraph, or LlamaIndex.
• Integrate AI solutions with enterprise CCaaS platforms, CRM systems, ticketing tools, and knowledge management systems.
• Develop agent orchestration, tool calling, context management, guardrails, and human-agent handoff workflows.
• Build scalable backend services, APIs, microservices, and real-time communication systems.
• Deploy and optimize AI services on AWS, Azure, or GCP.
• Implement monitoring, tracing, testing, evaluation, and performance optimization for production AI systems.
• Drive architecture decisions and ensure reliability, security, scalability, and low-latency performance.

Requirements:

• Hands-on experience with enterprise CCaaS platforms or equivalent contact center infrastructure.
• Practical experience building and deploying AI-powered voice agents or real-time conversational voice applications.
• Strong understanding of STT, TTS, streaming audio, telephony integrations, and voice orchestration.
• Experience developing chatbots, digital assistants, messaging workflows, and conversational applications.
• Strong hands-on experience with generative AI, LLM-based applications, RAG, tool calling, and agentic AI.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent.
• Strong programming skills in Python, Node.js, Java, or similar backend technologies.
• Experience building and deploying production-grade AI systems with enterprise integrations.

Preferred Skills:

• CCaaS platforms: Genesys Cloud CX, Amazon Connect, NICE CXone, Five9, Twilio Flex, Cisco Webex Contact Center, or Talkdesk.
• Voice AI platforms: ElevenLabs, Deepgram, LiveKit, Vapi, or Retell AI.
• Conversational AI platforms: Dialogflow CX, Cognigy, Kore.ai, or Yellow.ai .
• Enterprise integrations with Salesforce, Zendesk, ServiceNow, or Freshdesk.
• Experience with multi-agent systems, human-in-the-loop workflows, and AI evaluation frameworks.

Ideal Candidate:

• A hands-on AI engineer or architect who has built and deployed production-grade voice and digital AI solutions integrated with enterprise contact center systems.
• Note: Candidates with only generic LLM, chatbot, or POC experience without practical CCaaS and voice AI exposure may not be a suitable fit.