🏢 Summary: Remote Staff Backend / Database Infrastructure Engineer role for a hands-on systems engineer to architect a purpose-built database and scale voice-AI infrastructure to 100,000+ concurrent calls. The offer includes $160,000–$240,000 USD base salary, 0.2%–1% equity, and the option to remain an individual contributor.
🗂️ Requirements: 5+ years of production backend engineering experience, Database, queue, indexing, or large-scale data-system development experience, Storage, ingestion, and query-path expertise, Distributed-systems design and production scaling experience, Quantifiable production-systems experience, End-to-end technical ownership, Architectural judgment and rapid iteration, Autonomous work in ambiguous startup environments, Written and verbal English, Daily AI coding-tool usage, Substantial daily US working-hours overlap
📃 Skills: Backend, Databases, Queues, Indexing, Storage, Ingestion, Querying, DistributedSystems, Claude, Codex, Cursor
🏢 Description: Staff Backend / Database Infrastructure Engineer
Remote — Europe, Canada, United States, or other locations with reasonable US time-zone overlap. Substantial daily overlap with US working hours is required. Candidates in Europe should be comfortable working late afternoons and part of the evening. Hybrid work is available in Austin or San Francisco.
Compensation
• Base salary: $160,000–$240,000 USD
• Equity: 0.2%–1%
• Final offer depends on seniority, location, experience, and level of technical ownership.
Description
Join a small, senior engineering team building database and backend infrastructure for a QA platform for AI voice agents. The platform supports pre-deployment simulations, production monitoring, observability, and automated red-teaming, and is scaling from thousands toward 100,000+ concurrent calls, with a longer-term path to one million.
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 ambiguous problems through production deployment.
• Help establish the technical direction for a long-term platform.
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 of meaningful system components.
• Ability to build complete systems, not only narrowly scoped components.
• Strong architectural judgment and 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.
Strong Advantages
• Experience as a founding engineer, first or second engineer, or one of the first ten startup hires.
• Experience at a modern database, data infrastructure, or observability company.
• Open-source contributions to PostgreSQL, ClickHouse, Redis, Kafka, Temporal, LiveKit, or similar infrastructure projects.
• 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 that process gigabytes or terabytes of data daily.
• 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. Deep systems engineering capability is prioritized over voice-domain experience.
How the Team Operates
This is a small, senior, highly technical team. The team ships multiple times per day and follows a simple model: define the problem, identify options, select the cheapest useful experiment, assign ownership, ship, and iterate.
The environment suits engineers who value autonomy, ambiguity, and direct responsibility. It is not a strong match for candidates who need lengthy onboarding, extensive organizational structure, or a large support team before contributing. The role can remain a highly technical individual-contributor position; future management responsibilities are available but not required.
Interview Process
The 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.
Application
Apply with a CV or LinkedIn profile. Include a short example of the most complex database, queue, indexing, or large-scale backend system personally built or owned, including its scale and individual contribution where possible.
