Backend Engineer - SDE 2 (Voice AI / Telephony Platform)
Backend Engineer - SDE 2 (Voice AI / Telephony Platform)
blue machines ai2-4 Years
- Posted 2 hours ago
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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
Must-Have Skills
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
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
