Lead Engineer

Blue Machines AI; Bengaluru; Presencial; INR 4.000.000 - 9.000.000; Jornada completa

Descripción de la vacante

Blue Machines AI is seeking a Lead Engineer to own the real-time voice and telephony platform powering live AI conversations. You will set the technical direction from carrier signalling to the AI agent, with hands-on coding 50–70% of the time and leadership for a team of 3–6 engineers.

You will mentor, design scalable media pipelines, ensure low-latency end-to-end delivery, and collaborate with ML teams to advance in-house AI models. Bengaluru-based, full‑time role.

Formación

• 7–10 years of backend development in Python or Java for high-scale, low-latency systems.
• Proven tech lead guiding a team of 3–6 engineers while remaining hands-on.
• Deep expertise in SIP, RTP/SRTP, SDP and WebRTC.
• Built or operated media/signalling stacks such as FreeSWITCH, Asterisk, Kamailio/OpenSIPS or LiveKit.
• Experience with carrier integrations and SIP trunking; CPaaS like Twilio/Exotel/Plivo.
• Strong knowledge of audio codecs, NAT traversal; debugging with Wireshark/sngrep.
• Experience shipping Voice AI with streaming ASR/TTS and latency tuning.
• Experience integrating LLMs, vector DBs or AI agent frameworks.
• System design and distributed systems ownership with scalability focus.
• Cloud infra, databases, queues; Kubernetes and Docker deployments.
• Eligible to work in India.

Responsabilidades

• Own end-to-end architecture of voice and telephony stack from carrier to AI agent.
• Design and run real-time media pipelines that stream audio to ASR/LLM/TTS with low latency.
• Lead carrier and telephony integrations: SIP trunks, DIDs, provisioning, multi-provider failover.
• Define and own SLOs for latency, uptime and call success rate.
• Scale platform for high concurrency via Kubernetes autoscaling and cost per call minute.
• Set engineering bar: code/design reviews, build-vs-buy decisions, debt management.
• Lead and mentor a team of 3–6 engineers; plan, break down work, hire.
• Own production health: observability (Datadog, Sentry), on-call, incident response, postmortems.
• Collaborate with product and AI on multi-agent orchestration and automation.
• Work with ML to integrate in-house models, benchmarking and evaluation.

Conocimientos

Backend development (Python/Java)

Tech lead experience

SIP/RTP/SRTP/WebRTC

Media/Signalling stacks (FreeSWITCH/A_

Herramientas

FreeSWITCH

Asterisk

Kamailio/OpenSIPS

LiveKit

WebRTC

Wireshark

sngrep

Kubernetes

Docker

Descripción del empleo

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.

Must‑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.