Note: The job is a remote job and is open to candidates in USA. AIDA projektai is recruiting for a rapidly growing technology company building infrastructure for AI-powered voice agents. The Senior/Staff Backend Engineer will design a purpose-built conversational AI database, scale real-time voice simulation infrastructure to 200K+ concurrent calls, and own highly available backend and distributed data systems. The role also involves building ingestion pipelines, improving observability, and optimizing production performance and reliability.
Responsibilities
- Design and build a **purpose-built database for conversational AI data**, including storage architecture, indexing, ingestion, query paths, and retrieval at scale
- Scale simulation infrastructure from approximately **30K toward 200K+ concurrent voice calls**
- Architect systems for high availability, graceful degradation, and **99.99% uptime**
- Own critical backend services built primarily with **TypeScript/Node.js and Python**
- Work with technologies across real-time voice and AI infrastructure, including **LiveKit, Temporal, STT/TTS systems, and LLM tooling**
- Build reliable pipelines for telephony events, recordings, transcripts, evaluations, and call outcomes
- Improve distributed tracing and production observability using technologies such as **OpenTelemetry and SigNoz**
- Diagnose and eliminate performance bottlenecks across high-throughput distributed systems
- Make architectural decisions around scalability, reliability, latency, storage, and infrastructure costs
- Ship quickly, measure production behavior, and continuously iterate. The engineering team currently deploys to production multiple times per day
Skills
- 5+ years of software engineering experience, with strong backend or infrastructure expertise
- Proven experience building a database, queue, storage engine, streaming system, distributed data platform, or comparable large-scale infrastructure
- Ideally, you were a primary author, architect, or technical owner rather than simply a user or contributor
- Strong knowledge of distributed systems, including partitioning, replication, concurrency, consistency, failure recovery, backpressure, and graceful degradation
- Experience scaling infrastructure under significant real-world production load
- Ability to discuss previous systems quantitatively — for example, requests/events per second, concurrency, p95/p99 latency, data volumes, availability, cluster size, or cost improvements
- Strong backend development experience. TypeScript/Node.js and Python are used on the project, but engineers from other strong infrastructure backgrounds are welcome
- Strong understanding of production monitoring, observability, and distributed tracing
- High level of ownership and ability to operate effectively in a fast-moving environment
- AI-native mindset: actively using modern AI tools to accelerate engineering, debugging, research, and development
- Strong bias to action — comfortable building the smallest working solution, shipping it, learning from production, and iterating
- Database internals / storage engine development
- Distributed databases
- Kafka, Pulsar, Redpanda, or similar messaging infrastructure
- Streaming or high-throughput ingestion systems
- Query engines and indexing
- Observability infrastructure
- OpenTelemetry / SigNoz
- WebRTC / LiveKit
- Telephony, SIP, or RTP
- Voice or audio processing
- STT/TTS infrastructure
- LLM infrastructure
- Experience at a database, data infrastructure, observability, or developer infrastructure company
Benefits
- Meaningful equity
- Paid work trial based on a real engineering problem
Company Overview