Staff Backend / Database Infrastructure Engineer
New
T
TalenticaAI Infrastructure
Europe, Canada or United States, Substantial daily overlap with US working hours required.Full-TimeStaff
Salary$160,000–$240,000 USD base + 0.2%–1% equity
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Job Details
- Languages
- Clear written and verbal English communication.
- Experience
- At least 5 years of production backend engineering experience.
- Required Skills
- AWSNode.jsPostgreSQLKafkaTypeScriptClickhouseRedisScalaDistributed Systems
Requirements
- At least 5 years of production backend engineering experience.
- Hands-on experience building or core-contributing to a database, queue, indexing layer or large-scale data system.
- Strong understanding of storage, ingestion and query paths.
- Experience designing and scaling distributed systems under real production load.
- Ability to discuss previous systems quantitatively, including throughput, data volume, latency, SLAs, bottlenecks and failure modes.
- Evidence of personal ownership in designing and building meaningful system components.
- Ability to build complete systems rather than work only on narrowly scoped components.
- Strong architectural judgment combined with a bias toward shipping and iteration.
- Experience operating without extensive process, detailed specifications or organizational scaffolding.
- Clear written and verbal English communication.
- Daily use of AI coding tools such as Claude Code, Codex or Cursor.
- Availability for substantial daily overlap with US working hours.
Responsibilities
- Lead the design and development of a purpose-built database and indexing architecture.
- Scale the simulation engine toward 100,000+ concurrent voice calls.
- Build high-throughput ingestion, storage and query infrastructure.
- Develop systems for processing call recordings, transcripts, metadata and evaluation results.
- Improve reliability, latency and performance across the platform’s highest-load paths.
- Build infrastructure supporting AI red-teaming and production monitoring.
- Make key architectural decisions and turn them into working prototypes quickly.
- Own projects end-to-end, from an ambiguous problem to production deployment.
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