Lead Backend Engineer - Voice AI

Qrata; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Qrata is seeking a hands-on Lead Backend Engineer – Voice AI to own backend foundations of our Voice AI product in Bengaluru, India. You will design and build scalable, low-latency services for telephony, audio streaming, and orchestration, with a strong emphasis on real-time performance and reliability.

You will mentor a growing team, collaborate with Product and Design, and drive end-to-end features from zero to production while balancing speed, UX, latency, security, and costs.

Qualifications

• Hands-on backend engineer with 5–8 years in customer-facing production systems.

Responsibilities

• Lead design, development, and evolution of backend systems powering real-time Voice AI experiences.

Skills

Python

FastAPI

PostgreSQL

Redis

APIs

Distributed systems

Voice AI

Leadership

Communication

Observability

Tools

LiveKit

Vapi

Twilio

WebRTC

LangChain

LangGraph

Docker

CI/CD

Job description

Work mode: 5 days/week, Work from Office

Experience: 5-8 years

MUST HAVE - Voice AI OR VoiceBot AND Python

The Role

We are looking for a hands-on Lead Backend Engineer – Voice AI to build and own the backend foundations of our Voice AI product.

What You’ll Do

• Lead the design, development, and evolution of backend systems that power real-time Voice AI experiences.
• Build reliable, low-latency services for telephony, audio streaming, conversation orchestration, session management, and post-call workflows.
• Develop and operate Voice AI integrations using platforms such as LiveKit, Vapi, Twilio, WebRTC, or similar technologies.
• Integrate speech-to-text, text-to-speech, LLMs, retrieval systems, and AI evaluation pipelines into robust production workflows.
• Build agentic and conversational workflows using tools such as LangChain, LangGraph, or equivalent frameworks.
• Design scalable APIs, event-driven workflows, data models, background jobs, and fault-tolerant systems.
• Own backend services built with Python, FastAPI, PostgreSQL, Redis, queues, and cloud infrastructure.
• Lead, mentor, and grow a high-performing team of talented engineers; create clarity, set a high execution bar, and enable the team to deliver ambitious outcomes in a fast-moving environment.
• Partner with Product and Design to identify customer problems, define requirements, run experiments, and ship end-to-end features.
• Make thoughtful trade-offs across speed, product experience, latency, reliability, security, scalability, and cost.
• Establish strong observability across the platform, including logging, monitoring, alerting, tracing, and meaningful product/quality metrics.
• Define and improve metrics such as call success rate, latency, conversation completion, AI quality, and user satisfaction.
• Raise the engineering bar through architecture reviews, code reviews, documentation, and mentorship.

What We’re Looking For

• 5-8 years of backend engineering experience, including ownership of customer-facing production systems.
• Strong proficiency in Python and backend frameworks such as FastAPI.
• Strong experience with relational databases, especially PostgreSQL, along with caching and asynchronous processing using tools such as Redis, queues, and background workers.
• Experience designing scalable APIs, distributed systems, asynchronous workflows, and event-driven architectures.
• Hands‑on experience with Voice AI, conversational AI, telephony, WebRTC, real‑time communications, or audio/video streaming systems.
• Experience with platforms or tools such as LiveKit, Vapi, Twilio, or similar Voice AI and communications technologies.
• Practical experience building LLM‑powered applications, including prompt orchestration, tool calling, RAG, structured outputs, and AI evaluation/monitoring.
• Experience with LangChain, LangGraph, or comparable agentic workflow frameworks.
• Familiarity with cloud infrastructure, Docker, CI/CD, monitoring, logging, tracing, and
• Strong product mindset: you care deeply about user experience, customer outcomes, and business impact, not just clean code.
• Ability to thrive in ambiguity, independently define a path forward, and take ideas from zero to production.
• Strong communication skills and the ability to work effectively across Engineering, Product, Design, and AI/ML teams.
• Demonstrated experience leading or managing a strong engineering team, including technical direction, prioritization, mentoring, performance coaching, and creating an environment of high ownership and accountability.