Staff Backend / Database Infrastructure Engineer
First seen by Alion on Oct 6, 2026.
Staff Backend / Database Infrastructure Engineer
Remote | Europe, Canada or United States | US working-hours overlap required
Compensation: $160,000–$240,000 USD base + 0.2%–1% equity
We are recruiting for a fast-growing, YC-backed US startup building infrastructure for the voice AI ecosystem.
The company provides a complete QA platform for AI voice agents, covering pre-deployment simulations, production monitoring, observability and automated red-teaming. Its technology has already analyzed more than 5 million production calls and tested over 10,000 voice agents, including deployments within regulated industries such as financial services and healthcare.
The engineering team is now entering a critical stage: building its own database and scaling the platform from thousands toward 100,000+ concurrent calls, with a longer-term path to one million.
We are looking for a highly hands-on Staff-level engineer who can lead database and backend architecture, build complex systems end-to-end and operate effectively 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: you personally designed and built meaningful parts of the 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, together with a practical understanding of their strengths and trade-offs.
Availability for substantial daily overlap with US working hours. For candidates based in Europe, this means working during the late afternoon and part of the evening.
We care more about technical depth, judgment and measurable impact than a specific title, programming language or number of years in one particular stack.
Strong advantages
Experience as a founding engineer, first or second engineer, or one of the first ten hires at a startup.
Experience within a modern database, data infrastructure or observability company.
Open-source contributions to projects such as 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 of your primary employment.
Voice and telephony experience is not required. The company would rather teach the voice domain to an exceptional systems engineer than try to teach deep systems engineering to a domain specialist.
How the team operates
This is a small, senior and highly technical engineering team. The founder remains hands-on and writes production code.
The team ships multiple times per day and values a simple operating model:
Define the problem, identify the options, select the cheapest useful experiment, assign ownership, ship and iterate.
This environment is best suited to engineers who enjoy autonomy, ambiguity and direct responsibility. It will not be 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 are available in the future but are not required.
Location
The position is remote and open to candidates based in:
Europe
Canada
United States
Other locations offering reasonable US time-zone overlap
Regular and meaningful overlap with US working hours is mandatory. Candidates based in Europe should be comfortable working later hours to collaborate with the US team.
The company also has office locations in Austin and San Francisco for candidates who prefer a hybrid environment.
Compensation
Base salary: $160,000–$240,000 USD
Equity: 0.2%–1%
The final offer will depend on seniority, location, experience and the level of technical ownership the candidate can take on.
Interview process
The complete process typically takes approximately two weeks:
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.
Interested?
Apply with your CV or LinkedIn profile.
Please include one short example of the most complex database, queue, indexing or large-scale backend system you personally built or owned. If possible, mention its scale and your individual contribution.
Tech stack
- TypeScript
- Node.js
- Distributed systems
- PostgreSQL
- Kafka
- AWS
- Scala