Lead Engineer

Posted 6 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Expert/Leader
Artificial Intelligence • Software • Conversational AI
The Role
Lead the architecture and development of a high-scale real-time voice and telephony platform for AI conversations. Own SIP, media pipelines, WebRTC, carrier integrations, call quality, latency, reliability, Kubernetes scaling, observability, and production operations. Lead and mentor 3–6 engineers while remaining hands-on, partnering with product and ML teams to integrate ASR, TTS, LLMs, and multi-agent orchestration.
Summary Generated by Built In
About Blue Machines

Blue Machines builds Voice AI and Agentic Automation systems that change how enterprises around the world interact with AI. Our platform runs live voice conversations at global scale, combining real-time telephony, in-house AI models and multi-agent orchestration. We're a world-class team building real-time systems that push the limits of latency and reliability.

Role Overview

We're looking for a Lead Engineer to own the real-time voice and telephony platform that powers live AI conversations at Blue Machines. You'll set the technical direction for everything from the carrier and SIP trunk to the AI agent: signalling, media, streaming ASR/TTS and the latency budget across all of them.

This is a hands-on leadership role. You'll spend most of your time (around 50–70%) designing and building, while leading and mentoring a team of 3–6 engineers.

Responsibilities
  • Own the end-to-end architecture of the voice and telephony stack, covering SIP signalling, media servers, WebRTC and call routing from the carrier to the AI agent.
  • Design and run real-time media pipelines (FreeSWITCH, Asterisk, Kamailio or LiveKit) that stream audio to ASR, LLM and TTS within tight end-to-end latency budgets.
  • Lead carrier and telephony-provider integrations: SIP trunks, DIDs, number provisioning and multi-provider failover.
  • Drive call quality and reliability across codecs, jitter, packet loss, echo and barge-in. Define and own SLOs for latency, uptime and call success rate.
  • Scale the platform for high call concurrency through capacity planning, autoscaling of media workloads on Kubernetes and cost per call minute.
  • Set the engineering bar for the team: lead system design, review code and designs, make build-vs-buy calls and manage tech debt.
  • Lead and mentor a team of 3–6 engineers. Plan and break down work, grow engineers through feedback and take part in hiring.
  • Own production health for live call traffic, including observability (Datadog, Sentry), on-call, incident response and postmortems.
  • Partner with product and AI teams on the platform's multi-agent orchestration and automation layer.
  • Work closely with the ML team to integrate in-house models, drive benchmarking and evaluation, and help build the next generation of in-house AI models.

RequirementsMust-Have Skills
  • 7–10 years of backend development experience in Python or Java, including time spent building high-scale, low-latency real-time systems.
  • Proven experience as a tech lead: guiding a team through design and delivery, mentoring engineers and staying hands-on in the codebase while leading a team of 3–6 engineers.
  • Deep, hands-on expertise in SIP, RTP/SRTP, SDP and WebRTC.
  • Has built or operated media and signalling stacks such as FreeSWITCH, Asterisk, Kamailio/OpenSIPS or LiveKit in production.
  • Experience with carrier integrations and SIP trunking, plus CPaaS providers such as Twilio, Exotel or Plivo.
  • Strong grasp of audio codecs and NAT traversal, and debugging call quality using tools such as Wireshark or sngrep.
  • Experience shipping Voice AI in production: streaming ASR/TTS, real-time inference and end-to-end latency tuning.
  • Experience integrating LLMs, vector DBs or AI agent frameworks into production systems.
  • Strong command of system design, concurrency and distributed systems, with a track record of owning architecture decisions.
  • Experience with cloud infrastructure, databases, and message queues, plus containerized deployments with Kubernetes and Docker.
  • Eligible to work in India.
Good to Have
  • Prior work leading AI-driven or telephony-driven platforms at scale.
  • Experience building contact-centre, IVR or outbound dialer systems.
  • Experience collaborating with ML/research teams on model benchmarking, evaluation or observability.
  • Contributions to open-source telephony or WebRTC projects.

Skills Required

  • 7–10 years of backend development experience in Python or Java, including high-scale, low-latency real-time systems
  • Experience as a technical lead guiding design and delivery, mentoring engineers, and remaining hands-on with a team of 3–6 engineers
  • Hands-on expertise in SIP, RTP/SRTP, SDP, and WebRTC
  • Production experience with FreeSWITCH, Asterisk, Kamailio, OpenSIPS, or LiveKit
  • Experience with carrier integrations, SIP trunking, and CPaaS providers such as Twilio, Exotel, or Plivo
  • Strong knowledge of audio codecs and NAT traversal, including call-quality debugging with Wireshark or sngrep
  • Production experience shipping Voice AI, including streaming ASR/TTS, real-time inference, and latency tuning
  • Experience integrating LLMs, vector databases, or AI agent frameworks into production systems
  • Strong system design, concurrency, and distributed systems experience with architecture ownership
  • Experience with cloud infrastructure, databases, message queues, Kubernetes, and Docker
  • Eligible to work in India
  • Experience leading AI-driven or telephony-driven platforms at scale
  • Experience building contact-center, IVR, or outbound dialer systems
  • Experience collaborating with ML or research teams on model benchmarking, evaluation, or observability
  • Contributions to open-source telephony or WebRTC projects
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The Company
89 Employees
Year Founded: 2025

What We Do

Blue Machines AI is an enterprise agentic customer-experience platform that deploys multilingual voice AI agents to automate customer conversations and service or sales workflows. Its platform orchestrates speech-to-text, text-to-speech and language models to support reliable, low-latency interactions at scale. It extends customer engagement across voice, chat, WhatsApp, web and email, adapting journeys toward defined outcomes. The company focuses on making AI production-ready for high-stakes enterprise use.

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