5+ IVR Jobs in India

Role Overview

We are looking for a hands-on Senior Telephony Engineer who actively writes production-grade code and has deep experience with Asterisk-based systems, Java backend development, and high-scale dialler platforms.

Key Responsibilities

This is NOT an architecture-only role we need someone who can:

• Write code
• Debug real-time call issues
• Build and optimize telephony flows end-to-end
• Key Responsibilities (Hands-on Coding Focus)
• Develop and maintain Asterisk dialplans, AGI scripts, and call flows
• Build Java-based backend services for telephony control and orchestration
• Implement and optimize predictive / preview / progressive diallers
• Integrate telephony stack with:

Kafka

RabbitMQ

• Write scalable code for call routing, retry logic, and queue handling
• Work directly on SIP signalling, RTP flows, and debugging call issues
• Handle real-time call events, CDR processing, and logging pipelines
• Optimize systems for high concurrency (thousands of parallel calls)
• Debug production issues like:

Call drops

Latency

One-way audio

SIP failures

Qualifications & Skills

• Bachelors degree in Computer Engineering; Masters is a plus.
• Telephony (Core Requirement)
• Strong hands-on experience with Asterisk
• Deep knowledge of:

SIP / RTP / VoIP

Dialplans

AGI / AMI

• Experience building or maintaining dialers (very important)
• Backend Development
• Strong coding skills in Java (Spring Boot preferred)
• Experience building microservices / APIs
• Comfortable writing high-performance, low-latency code
• Messaging & Event Systems
• Hands-on experience with:

Apache Kafka

RabbitMQ

• Ability to implement event-driven systems
• Scaling & Performance
• Experience handling high call volumes (1000+ concurrent calls)

Understanding of:

• Multi-threading
• Queue management
• Load handling
• Good to Have
• Experience with predictive dialers
• Exposure to WebRTC / real-time communication
• Experience with Docker / Kubernetes
• Understanding of TRAI / Indian telecom ecosystem
• Experience with FreeSWITCH (bonus)

What We Are NOT Looking For

• Pure solution architects who dont code
• People with only theoretical telecom knowledge
• Candidates without real dialer / Asterisk production experience

What We Are Looking For

Someone who has:

• Written real dialplans and backend code
• Debugged live call issues
• Worked on production telephony systems
• A problem solver who can go deep into logs, packets, and code

Impact of the Role

You will directly contribute to building a high-scale telephony + AI voice platform, working on real-time systems that handle thousands of concurrent calls.

About MyOperator

MyOperator is a Business AI Operator and category leader that unifies WhatsApp, Calls, and AI-powered chatbots & voice bots into one intelligent business communication platform.Unlike fragmented communication tools, MyOperator combines automation, intelligence, and workflow integration to help businesses run WhatsApp campaigns, manage calls, deploy AI chatbots, and track performance — all from a single no-code platform.Trusted by 12,000+ brands including Amazon, Domino’s, Apollo, and Razor-pay, MyOperator enables faster responses, higher resolution rates, and scalable customer engagement

Role Summary

We’re hiring a Front Deployed Engineer (FDE)—a customer-facing, field-deployed engineer who owns the end-to-end delivery of AI bots/agents.

This role is “frontline”: you’ll work directly with customers (often onsite), translate business reality into bot workflows, do prompt engineering + knowledge grounding, ship deployments, and iterate until it works reliably in production.

Think: solutions engineer + implementation engineer + prompt engineer, with a strong bias for execution.

Responsibilities

Requirement Discovery & Stakeholder Interaction

• Join customer calls alongside Sales and Revenue teams.
• Ask targeted questions to understand business objectives, user journeys, automation expectations, and edge cases.
• Identify data sources (CRM, APIs, Excel, SharePoint, etc.) required for the solution.
• Act as the AI subject-matter expert during client discussions.

Use Case & Solution Documentation

• Convert discussions into clear, structured use case documents, including:
• Problem statement & goals.
• Current vs. proposed conversational flows.
• Chatbot conversation logic, integrations, and dependencies.
• Assumptions, limitations, and success criteria.

Customer Delivery Ownership

Own deployment of AI bots for customer use-cases (lead qualification, support, booking, etc.). Run workshops to capture processes, FAQs, edge cases, and success metrics. Drive the go-live process: requirements through monitoring and improvement.

Prompt Engineering & Conversation Design

Craft prompts, tool instructions, guardrails, fallbacks, and escalation policies for stable behavior. Build structured conversational flows: intents, entities, routing, handoff, and compliant responses. Create reusable prompt patterns and "prompt packs."

Testing, Debugging & Iteration

Analyze logs to find failure modes (misclassification, hallucination, poor handling). Create test sets ("golden conversations"), run regressions, and measure improvements. Coordinate with Product/Engineering for platform needs.

Integrations & Technical Coordination

Integrate bots with APIs/webhooks (CRM, ticketing, internal tools) to complete workflows. Troubleshoot production issues and coordinate fixes/root-cause analysis.

What Success Looks Like

• Customer bots go live quickly and show high containment + high task completion with low escalation.
• You can diagnose failures from transcripts/logs and fix them with prompt/workflow/knowledge changes.
• Customers trust you as the “AI delivery owner”—clear communication, realistic timelines, crisp execution.

Requirements (Must Have)

• 2–5 years in customer-facing delivery roles: implementation, solutions engineering, customer success engineering, or similar.
• Hands-on comfort with LLMs and prompt engineering (structured outputs, guardrails, tool use, iteration).
• Strong communication: workshops, requirement capture, crisp documentation, stakeholder management.
• Technical fluency: APIs/webhooks concepts, JSON, debugging logs, basic integration troubleshooting.
• Willingness to be front deployed (customer calls/visits as needed).

Good to Have (Nice to Have)

• Experience with chatbots/voicebots, IVR, WhatsApp automation, conversational AI platforms with at least a couple of projects.
• Understanding of metrics like containment, resolution rate, response latency, CSAT drivers.
• Prior SaaS onboarding/delivery experience in mid-market or enterprises.

Working Style & Traits We Value

• High agency: you don’t wait for perfect specs—you create clarity and ship.
• Customer empathy + engineering discipline.
• Strong bias for iteration: deploy → learn → improve.
• Calm under ambiguity (real customer environments are chaotic by default).

About MyOperator

MyOperator is a Business AI Operator and category leader that unifies WhatsApp, Calls, and AI-powered chatbots & voice bots into one intelligent business communication platform.Unlike fragmented communication tools, MyOperator combines automation, intelligence, and workflow integration to help businesses run WhatsApp campaigns, manage calls, deploy AI chatbots, and track performance — all from a single no-code platform.Trusted by 12,000+ brands including Amazon, Domino’s, Apollo, and Razor-pay, MyOperator enables faster responses, higher resolution rates, and scalable customer engagement

Role Summary

We’re hiring a Front Deployed Engineer (FDE)—a customer-facing, field-deployed engineer who owns the end-to-end delivery of AI bots/agents.

This role is “frontline”: you’ll work directly with customers (often onsite), translate business reality into bot workflows, do prompt engineering + knowledge grounding, ship deployments, and iterate until it works reliably in production.

Think: solutions engineer + implementation engineer + prompt engineer, with a strong bias for execution.

Responsibilities

Requirement Discovery & Stakeholder Interaction

• Join customer calls alongside Sales and Revenue teams.
• Ask targeted questions to understand business objectives, user journeys, automation expectations, and edge cases.
• Identify data sources (CRM, APIs, Excel, SharePoint, etc.) required for the solution.
• Act as the AI subject-matter expert during client discussions.

Use Case & Solution Documentation

• Convert discussions into clear, structured use case documents, including:
• Problem statement & goals.
• Current vs. proposed conversational flows.
• Chatbot conversation logic, integrations, and dependencies.
• Assumptions, limitations, and success criteria.

Customer Delivery Ownership

Own deployment of AI bots for customer use-cases (lead qualification, support, booking, etc.). Run workshops to capture processes, FAQs, edge cases, and success metrics. Drive the go-live process: requirements through monitoring and improvement.

Prompt Engineering & Conversation Design

Craft prompts, tool instructions, guardrails, fallbacks, and escalation policies for stable behavior. Build structured conversational flows: intents, entities, routing, handoff, and compliant responses. Create reusable prompt patterns and "prompt packs."

Testing, Debugging & Iteration

Analyze logs to find failure modes (misclassification, hallucination, poor handling). Create test sets ("golden conversations"), run regressions, and measure improvements. Coordinate with Product/Engineering for platform needs.

Integrations & Technical Coordination

Integrate bots with APIs/webhooks (CRM, ticketing, internal tools) to complete workflows. Troubleshoot production issues and coordinate fixes/root-cause analysis.

What Success Looks Like

• Customer bots go live quickly and show high containment + high task completion with low escalation.
• You can diagnose failures from transcripts/logs and fix them with prompt/workflow/knowledge changes.
• Customers trust you as the “AI delivery owner”—clear communication, realistic timelines, crisp execution.

Requirements (Must Have)

• 2–5 years in customer-facing delivery roles: implementation, solutions engineering, customer success engineering, or similar.
• Hands-on comfort with LLMs and prompt engineering (structured outputs, guardrails, tool use, iteration).
• Strong communication: workshops, requirement capture, crisp documentation, stakeholder management.
• Technical fluency: APIs/webhooks concepts, JSON, debugging logs, basic integration troubleshooting.
• Willingness to be front deployed (customer calls/visits as needed).

Good to Have (Nice to Have)

• Experience with chatbots/voicebots, IVR, WhatsApp automation, conversational AI platforms with at least a couple of projects. 
• Understanding of metrics like containment, resolution rate, response latency, CSAT drivers.
• Prior SaaS onboarding/delivery experience in mid-market or enterprises.
• 
  

Working Style & Traits We Value

• High agency: you don’t wait for perfect specs—you create clarity and ship.
• Customer empathy + engineering discipline.
• Strong bias for iteration: deploy → learn → improve.
• Calm under ambiguity (real customer environments are chaotic by default).

About Vomyra:

We build Voice AI agents that answer business calls 24×7 for restaurants, hotels, spas, education centres, and service businesses. No more missed calls → higher revenue → better customer experience.

Role Overview:

You will own the full sales cycle: prospecting → demo → trial → closure. You’ll directly work with the founder, sell to SMB/MSME owners, and help them adopt Voice AI.

What you’ll do

Generate qualified leads through LinkedIn, WhatsApp outreach, and cold calling

Run product demos and explain value clearly to business owners

Convert trials to paid plans

Manage a predictable pipeline and follow-up rigor

Hit weekly KPIs (demos, trials, conversions)

Maintain CRM hygiene and report performance

Gather market insights, objections, and help improve messaging

Must-haves

2–5 years of SaaS / Cloud / IVR / Telephony sales

Strong communication in English + Hindi

Experience selling to SMEs/MSMEs (restaurants/hotels/spas = bonus)

High activity mindset: outreach, follow-up, hustle

Comfort with demos, objections, pricing conversations

Proven consistency in hitting targets

Good-to-haves

Experience with Exotel, MyOperator, Ozonetel, Airtel Tata Reliance Jio

Exposure to GenAI or Voice AI products

Startup or zero-to-one environment experience

Ability to work in fast cycles with direct founder access

What we offer

Competitive base + aggressive incentives

Fast growth: work directly with founder, own accounts

Flexible remote-friendly culture

Opportunity to be early in a rapidly growing Voice AI category

Location

Remote / Delhi-NCR preferred