Senior Backend Engineer - AI Infrastructure & Database Scaling
Own and scale the platform's infrastructure to handle 1,000 to 1,000,000 concurrent jobs, building an observability-to-database transition. Prototype and implement a purpose-built indexing engine and data layer. Report directly to CEO in a high-velocity, small-team environment.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Remote (US-hours overlap) | Austin or SF preferred | $140–250K base + 0.2–1% equity | Visa sponsorship available
I am partnering with a well-funded, early-stage AI infrastructure startup that builds the testing and observability layer for a fast-growing category of AI systems. The company has real revenue, marquee customers across regulated industries, and a small, senior engineering team that holds a serious reputation for shipping.
The role
You will own the infrastructure that scales the platform 10–100x over the next several months. The system handles roughly 1,000 concurrent jobs for most customers today, one customer already needs 100K, and the near-term target is a million, so the platform must climb two orders of magnitude in a matter of months.
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This is the point where an observability company becomes a database company, and you will own that transition. You will scale the existing system first, and then you will prototype and build the company's own indexing engine and purpose-built data layer, which becomes the core technical moat. You will report directly to the CEO on an eight-person team that ships to production multiple times a day.
The ramp follows a crawl-walk-run arc. In month one you will audit the system end-to-end and propose solutions, in month three you will prototype the internal indexing layer, and by month six you will have a working data layer that the platform builds on top of.
What they're looking for
- 5+ years of strong production backend in Python or TypeScript/Node
- You've owned real-time or near-real-time systems at scale: queues, streaming, low-latency APIs
- You've built or core-contributed to a real data system (Redis, Kafka, Postgres, ClickHouse, Temporal, a vector DB, or similar). This is the differentiator, not a nice-to-have
- You ship end-to-end: schema design, API, observability, on-call
- You're effective in a small team with no PM hand-holding and define your own scope
- AI-native in your workflow (Claude Code, Cursor, Codex)
- Bonus: you'd build a database for fun on a weekend, and you've got one specific area you're exceptional at; they build the role around the spike
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The honest version of the culture
The team runs at high intensity on short time horizons, with a decisive operating cadence and very low procrastination. The engineers would rather ship and iterate than debate a problem for days. This role is a genuinely strong fit for a builder who wants real ownership and high velocity, and it is a genuinely poor fit for someone who wants a slower, more deliberate pace, so it is worth being clear on that difference up front.
Comp and logistics
$140–250K base depending on level, 0.2–1% equity, flexible for an exceptional candidate. Remote-friendly with meaningful US-hours overlap; Austin or SF preferred but not required. Visa sponsorship available. 100% covered health, vision, and dental; all AI tools and tokens fully paid; quarterly offsites.
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