Staff Voice AI Engineer - Core Platform

Armis; Ahmedabad District; On-site; INR 350,000 - 700,000; Full time

Job summary

Armis is seeking a Staff Voice AI Engineer - Core Platform to design and implement a scalable Voice AI platform, spanning audio acquisition, conversation management, speech generation and model integration. You will partner with product managers to understand customer use cases and deliver reliable, production-grade systems across multiple regions.

You will mentor teammates, enforce best practices in code quality and testing, and help evolve SRE tooling for operational excellence in regulated

Qualifications

• 8+ years of relevant industry experience.
• Hands-on experience building distributed Voice AI systems at scale.
• 4+ years building LLM-based applications (integration, not training).
• 6+ years of development with Python, Golang, Java or similar.
• 2+ years building agents and LLМ-based experiences.
• Experience operating highly available distributed workloads on Kubernetes.
• Experience ensuring compliance and security in regulated environments is a plus.
• Proven track record shipping distributed Voice AI or voice platform systems.

Responsibilities

• Contribute to design, development and implementation of the core Voice Platform.
• Collaborate with product managers to understand customer use cases and build for success.
• Build and deploy large Voice AI distributed systems at scale across regions.
• Write clean, scalable code; participate in reviews and testing.
• Help improve SRE practices by turning operational use cases into tooling requirements.
• Mentor colleagues and promote knowledge-sharing across Voice AI teams.

Skills

Distributed systems

Python

Golang

Java

LLM integration

Prompt engineering

Kubernetes

DevOps

Voice AI

Compliance/Security

Mentoring

Claude Code

Cursor

Windsurf

Tools

Kubernetes

Job description

Job Description

As a Staff Voice AI Engineer - Core Platform you will:

• Contribute to the design, development and implementation of the core Voice Platform (Audio Acquisition, Conversation Management, Speech Generation, integration with API and self-hosted Voice AI models, Voice Harness)
• Partner with product managers to work with customers, understand their use cases and technology challenges, and build for their success
• Build and deploy large Voice AI distributed systems at scale spanning multiple regions and datacenters
• Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc.)
• Contribute to the continuous improvement of the SRE practice by turning operational use cases into requirements for software tooling
• Be a mentor for colleagues and help promote knowledge-sharing across Voice AI engineering disciplines Qualifications

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI s potential impact on the function or industry.
• 8+ year of relevant industry experience
• Hands-on experience building distributed Voice AI systems with a large operational scale
• ~4+ years building LLM-based applications (integrating models, not training)
• 6+ years of development experience with Python, Golang, Java, or similar languages.
• 2+ years of experience building agents (prompt engineering) and developing LLM-based experiences
• Working experience operating highly available distributed workloads on Kubernetes following a DevOps approach.
• Experience building software for compliance and security in regulated environments is considered an asset
• A proven track record of architecting and shipping distributed Voice AI or voice platform systems (real-time audio, STT/TTS, telephony or WebRTC) at large operational scale
• Critically thinking around AI integrations for work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AIs potential impact on the function or industry.
• Experience building with AI tools such as Claude Code, Cursor, Windsurf