Staff Backend / Database Infrastructure Engineer

Compensation

• Base salary: $160,000–$240,000 USD
• Equity: 0.2%–1%

The platform provides QA infrastructure for AI voice agents, including pre-deployment simulations, production monitoring, observability, and automated red-teaming. It has analyzed more than 5 million production calls and tested over 10,000 voice agents, including deployments in regulated industries such as financial services and healthcare.

The engineering team is building its own database and scaling the platform from thousands toward 100,000+ concurrent calls, with a longer-term path to one million. This is a hands-on Staff-level role leading database and backend architecture, building complex systems end-to-end, and operating within a small, fast-moving startup team.

What you will work on

• 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.
• Help establish the technical direction for a system that can become a long-term company moat.

What we are looking for

• 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: personally designed and built meaningful parts of a system.
• 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, with practical understanding of their strengths and trade-offs.
• Availability for substantial daily overlap with US working hours. Candidates based in Europe must work during the late afternoon and part of the evening.

Technical depth, judgment, and measurable impact matter more than a specific title, programming language, or number of years in a particular stack.

Strong advantages

• Experience as a founding engineer, first or second engineer, or one of the first ten hires at a startup.
• Experience at a modern database, data infrastructure, or observability company.
• Open-source contributions to PostgreSQL, ClickHouse, Redis, Kafka, Temporal, LiveKit, or similar infrastructure.
• Production experience with Scala, Rust, Haskell, or another systems-oriented language.
• Experience with voice technology, telephony, WebRTC, audio pipelines, or real-time communications.
• Experience building systems processing gigabytes or terabytes of data per day.
• Hands-on experience with PostgreSQL, Kafka, Redis, ClickHouse, Temporal, or custom indexing systems.
• Personal systems, database, or open-source projects built outside primary employment.

Voice and telephony experience is not required. The role prioritizes exceptional systems engineering depth over prior voice-domain experience.

How the team operates

This is a small, senior, highly technical engineering team. The founder remains hands-on and writes production code. The team ships multiple times per day and follows a simple operating model:

• Define the problem.
• Identify the options.
• Select the cheapest useful experiment.
• Assign ownership.
• Ship and iterate.

The environment suits engineers who enjoy autonomy, ambiguity, and direct responsibility. It is not a strong match for someone who requires several months of onboarding, extensive organizational structure, or a large support team before contributing.

The role can remain a highly technical individual-contributor position. Management responsibilities may be available in the future but are not required.

Location

• Remote work is open to candidates based in Europe, Canada, the United States, and other locations with reasonable US time-zone overlap.
• Regular, meaningful overlap with US working hours is mandatory.
• Candidates in Europe should be comfortable working later hours to collaborate with the US team.
• Hybrid work is available in Austin or San Francisco for candidates who prefer it.

Compensation

• Base salary: $160,000–$240,000 USD.
• Equity: 0.2%–1%.
• The final offer depends on seniority, location, experience, and the level of technical ownership the candidate can take on.

Interview process

• 15-minute introductory and culture conversation.
• Open-book backend coding interview using the candidate’s preferred AI tools.
• System design interview.
• Second system design interview.
• Optional paid two-to-three-day work trial if additional mutual validation is needed.
• Reference checks and offer.

The complete process typically takes approximately two weeks.

Apply with a CV or LinkedIn profile. Include one short example of the most complex database, queue, indexing, or large-scale backend system personally built or owned. Where possible, state its scale and individual contribution.