AI Solutions Engineer

CC33 Global Limited; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

CC33 Global Limited in Bengaluru is seeking an AI Solutions Engineer to turn our AI platform into working customer solutions. You will own implementation, design conversation flows, configure on the platform, and tune it until it holds up on real calls.

This is a delivery role with a high technical floor, focusing on workflow builders, prompts, knowledge bases, integration configuration and call logs without shipping product code. You will ensure successful deployments and post-launch tuning.

Qualifications

• 2–4 years of experience in solution delivery, implementation, technical support engineering, automation or conversational AI.
• Comfortable being the only technical person on a build — you unblock yourself instead of waiting.
• Able to read code and logs even if you don't write services: JSON, REST APIs, webhooks, Postman, browser dev tools, basic SQL, and enough Python or JavaScript to write a script or transform a payload.
• Hands‑on experience with at least one bot, workflow, iPaaS or automation platform — Dialogflow, Kore.ai, Yellow.ai, Voiceflow, Rasa, n8n, Zapier, Salesforce/ServiceNow flows or similar.
• Practical understanding of LLM behaviour — why a prompt fails, what changes the output, and how retrieval affects an answer.
• Structured debugging skills: you can look at a broken call and narrow down whether the problem is the prompt, flow, knowledge base or integration.
• Clear written English — you document what you build.
• Fluent in English and Hindi.

Responsibilities

• Build voice bots and chatbots on our platform: conversation flows, intent routing, fallback handling, escalation and transfer paths.
• Write and tune prompts for voice-first agents — token-efficient, multilingual (English / Hindi / Hinglish), and robust to real-world caller behaviour.
• Set up and curate knowledge bases that back retrieval-driven answers; diagnose and fix retrieval quality when answers go wrong.
• Configure integrations — telephony, WhatsApp, web chat, CRM and webhook endpoints — against documented APIs.
• Run test calls and simulations before go-live; analyse transcripts and call recordings to find where the bot breaks.
• Iterate post-launch on containment, latency and accuracy based on production call data.
• Write configuration and runbook documentation so a solution can be handed over and supported.
• Work with Parm to translate customer requirements into something buildable, and flag when a requirement needs platform work.

Skills

Bilingual EN/HI

Conversation design

Prompt engineering

Debugging skills

Tools

Dialogflow

Kore.ai

Yellow.ai

Voiceflow

Rasa

Zapier

n8n

Salesforce/ServiceNow flows

Job description

We have built the AI platform — voice bots, chatbots, agent copilots, knowledge retrieval and omni-channel engagement. What we need now is a team that turns that platform into working solutions for customers, quickly and repeatedly.

You will own implementation. Take a customer requirement, design the conversation flow, configure it on our platform, tune it until it holds up on real calls, and hand over something that works.

You are not building the platform — you are getting the most out of it.

This is a delivery role with a high technical floor. You will spend your day in workflow builders, prompts, knowledge bases, integration configuration and call logs. You will not be shipping product code.

What you’ll do

AI Solutions Engineer

Team:AI Solutions & Delivery

Location:Bangalore

Experience:2–4 years

About the role

We have built the AI platform — voice bots, chatbots, agent copilots, knowledge retrieval and omni-channel engagement. What we need now is a team that turns that platform into working solutions for customers, quickly and repeatedly.

You will own implementation. Take a customer requirement, design the conversation flow, configure it on our platform, tune it until it holds up on real calls, and hand over something that works.

You are not building the platform — you are getting the most out of it.

This is a delivery role with a high technical floor. You will spend your day in workflow builders, prompts, knowledge bases, integration configuration and call logs. You will not be shipping product code.

What you’ll do

• Build voice bots and chatbots on our platform: conversation flows, intent routing, fallback handling, escalation and transfer paths.
• Write and tune prompts for voice-first agents — token-efficient, multilingual (English / Hindi / Hinglish), and robust to real-world caller behaviour.
• Set up and curate knowledge bases that back retrieval-driven answers; diagnose and fix retrieval quality when answers go wrong.
• Configure integrations — telephony, WhatsApp, web chat, CRM and webhook endpoints — against documented APIs.
• Run test calls and simulations before go-live; analyse transcripts and call recordings to find where the bot breaks.
• Iterate post-launch on containment, latency and accuracy based on production call data.
• Write configuration and runbook documentation so a solution can be handed over and supported.
• Work with Parm to translate customer requirements into something buildable, and flag when a requirement needs platform work.

What you won’t do

• Own or ship platform services.
• Manage the customer relationship, commercials or scope — Parm and the commercial team own this.
• Build custom models or infrastructure.

What we’re looking for

• 2–4 years of experience in solution delivery, implementation, technical support engineering, automation or conversational AI.
• Comfortable being the only technical person on a build — you unblock yourself instead of waiting.
• Able to read code and logs even if you don't write services: JSON, REST APIs, webhooks, Postman, browser dev tools, basic SQL, and enough Python or JavaScript to write a script or transform a payload.
• Hands‑on experience with at least one bot, workflow, iPaaS or automation platform — Dialogflow, Kore.ai, Yellow.ai, Voiceflow, Rasa, n8n, Zapier, Salesforce/ServiceNow flows or similar.
• Practical understanding of LLM behaviour — why a prompt fails, what changes the output, and how retrieval affects an answer.
• Structured debugging skills: you can look at a broken call and narrow down whether the problem is the prompt, flow, knowledge base or integration.
• Clear written English — you document what you build.
• Fluent in English and Hindi.

Good to have

• Contact centre or CX domain experience — call flows, IVR, CSAT, containment and AHT.
• Exposure to telephony concepts such as SIP, WebRTC, Twilio or Asterisk.
• Experience with speech systems — ASR accuracy, TTS quality, barge-in and latency.
• Prompt engineering experience for production systems, not just experimentation.
• Experience delivering solutions to enterprise customers in BFSI, e-commerce or edtech.

Your first 90 days

30 days:Trained on the platform, shadowing an active build, and owning small configuration changes end-to-end.

60 days:Delivering a full use case with review — flow, prompts, knowledge base, integrations and test calls.

90 days:Owning an implementation independently, from requirement to go-live to post-launch tuning.

Why this role

You will work on production conversational AI running at scale for large consumer brands — not demos. The problems are real: latency, containment, multilingual accuracy, and caller behaviour that no test script predicts.

You will see many use cases across multiple industries in a year, giving you a faster learning curve than most product teams can offer.

Fast-paced career progression.This is a high-ownership team where strong performers can take on larger and more complex implementations quickly. As the AI Solutions & Delivery function grows, there will be opportunities to expand your scope, lead major deployments and grow with the team.

Join an AI business that already operates at scale.You will be working for an AI development business with thousands of customers already using its technology. You get the pace, ownership and learning of a fast-moving AI company, backed by a large existing customer base and real production use cases.

If you want to build a career in applied AI by solving real customer problems — and see the impact of your work in production — this is the role.