Senior/Staff Backend Engineer
$160,000–$240,000 year
RemoteUnited Kingdom or United States
Job Summary
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 while architecting systems for high availability, graceful degradation, and 99.99% uptime. Own critical backend services built primarily with TypeScript/Node.js and Python, working with technologies across real-time voice and AI infrastructure including LiveKit, Temporal, and LLM tooling. Build reliable pipelines for telephony events, recordings, transcripts, evaluations, and call outcomes. Improve distributed tracing and production observability using OpenTelemetry and SigNoz, diagnosing and eliminating 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 in an environment where the team deploys to production multiple times per day.
Required Qualifications
- 5+ years of software engineering experience
- 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
- 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
Desired Qualifications
- 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
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