Why this role stands out
This role offers a fantastic opportunity to build cutting-edge, high-scale backend systems for a leading Voice AI platform, providing significant growth and skill development in real-time communication and AI integration. You'll thrive here if you have 2-4 years of backend experience and a passion for distributed systems and real-time protocols, so consider applying to contribute to groundbreaking technology.
Quick overview
Job description
SDE II, Backend — Voice AI & Telephony
Experience: 2–4 Years
Location: Bengaluru (Work from Office)
Team: Blue Machines
Role Overview
We’re looking for an SDE II (Backend) to help build high-scale, low-latency systems for our AI and voice platform. You’ll work on real-time backend systems that power live voice conversations — combining strong backend fundamentals with exposure to WebRTC, SIP-based telephony, and Voice AI.
Responsibilities
- Build and maintain scalable microservices and backend systems that power real-time AI and voice workflows.
- Contribute to system design — APIs, data models, deployment, and monitoring — alongside senior engineers.
- Write performant, concurrent, fault-tolerant code at scale.
- Implement observability and testing best practices (Datadog, Sentry, etc.).
- Collaborate with product and AI teams on the platform’s multi-agent orchestration and automation layer.
- Partner closely with the ML team to integrate in-house models, support benchmarking and observability, and help build the next generation of in-house AI models.
Requirements
Must-Have Skills
- 2–4 years of backend development experience in Python or Java.
- Strong grasp of system design, concurrency, and distributed systems.
- Experience building scalable APIs or streaming systems.
- Familiarity with WebRTC, SIP, RTP, or other real-time communication protocols.
- Experience working with Voice AI or speech processing systems (ASR/TTS, real-time inference).
- Experience integrating LLMs, vector DBs, or AI agent frameworks into production systems.
- Experience with cloud environments (GCP/AWS) and containerized deployments (Kubernetes, Docker).
- Sound understanding of databases (MongoDB, Redis, Postgres) and message queues (Kafka, Pub/Sub).
- Collaborate with product and AI teams to evolve the platform’s multi-agent orchestration and automation layer.
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