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Platform Engineering

Job in New York, New York County, New York, 10261, USA
Listing for: Worky
Full Time position
Listed on 2026-08-15
Job specializations:
  • Software Development
    Backend Developer, Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 220000 - 280000 USD Yearly USD 220000.00 280000.00 YEAR
Job Description & How to Apply Below
Location: New York

Senior Software Engineer - Platform Engineering
About Santé

Santé is the #1 operating system for local retailers.

Our platform runs the entire store – point of sale, integrated payments, eCommerce, inventory management, delivery-app integrations, marketing, bookkeeping, and AI Agents – so the owners of liquor, grocery, and convenience stores can compete like the big chains without losing what makes them local.

We're building a future where the corner liquor store has better technology than the national retailer: one place for selling to customers everywhere with AI agents that spots slow-moving inventory and creates the promotion to move it. Every feature we ship lands in real stores the same week, and the feedback loop is direct – our customers call us by name.

We move fast and ship daily. AI-assisted engineering isn't a talking point here; agents like Devin, Claude, and Codex are part of how the team works every day, and engineers who master that leverage ship multiples of what they could alone.

About the Team

Platform Engineering owns the foundation everything else at Santé is built on:
Observability, Architecture, and POS / Checkout.

When a customer taps a card at a card terminal, this team's code decides whether that moment is instant, correct, and durable — through processor hiccups, database stress, and real-world edge cases. When any other team ships, this team's telemetry is how we know it worked. Platform Engineering is small by design and force-multiplied by tooling: its members carry the deepest context in the company and set the technical standards every other team builds on.

About the Role

You'll be a technical owner on the systems where correctness is non-negotiable: the sale write path, the payments integration layer, the database fleet, and the observability stack. This means working from ambiguous production signals ("this store's drawer count is off by $0.47") down to root cause, then designing the fix so the whole class of bug disappears. You'll partner with every other team — Money Movement, Merchant Experience, and Applied AI all build on your primitives — and with real store owners whose businesses run on what you ship.

Beyond building, you'll establish the patterns (idempotency, transactional boundaries, caching, instrumentation) that the rest of engineering adopts.

In this role, you will
  • Own the sale write path — the transactional core that records every sale in every store — including idempotency guarantees, race-condition elimination, split-payment correctness, and graceful degradation under database stress
  • Drive payments reliability end to end: card terminal terminal integrations, processor routing, preauth recovery, retries and reconciliation when the processor or the network misbehaves
  • Lead our observability program on Datadog — APM, RUM, and DBM with full log/trace correlation, structured logging with PII redaction, and the monitors and DORA metrics every team runs on
  • Hunt performance across a busy Postgres fleet: read-replica strategy, query-plan and index work, N+1 elimination, and caching layers (Elasti Cache) that hold up on the year's biggest sales days
  • Establish architectural patterns for multi-location retailers, offline-resilient POS, and high-write transactional workloads — and drive their adoption across teams
  • Multiply your output with AI agents: direct, review, and product ionize agent-written code as a core part of your workflow
Your background looks something like this
  • 5+ years building production software, with deep experience in Type Script/Node full-stack systems
  • Real depth in PostgreSQL: you read query plans for fun, know when an index helps and when it hurts, and have operated replicas under load
  • Distributed-systems instincts — idempotency keys, transactional boundaries, race conditions, and retry semantics are second nature
  • Experience owning observability for a production system (Datadog, or equivalent with Open Telemetry)
  • A bias for root cause over patch, and a track record of turning one-off incidents into eliminated bug classes
  • Comfort operating with high ownership in a small team where your decisions become the standard
Even better
  • Payments experience: EMV…
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