Full-Stack / Platform Engineer (High-Throughput Systems)

About the role
We are looking for a versatile engineer to build and scale a high-concurrency, multi-service platform. Our system powers real-time user interactions, sensitive financial transactions, and complex state management. You will work across a stack of web apps, APIs, and background workers where sub-second latency and data integrity are non-negotiable. We value engineers who prioritize clear service boundaries, safe schema migrations, and highly observable production environments.

What you’ll do
Real-Time UIs: Develop and maintain Next.js / React frontends that handle streaming data and high-frequency state updates.

Service Architecture: Design Node.js (Express-style) HTTP APIs and TypeScript services that manage complex user sessions and event-driven workflows.

Database Ownership: Manage PostgreSQL modeling and queries, ensuring high-performance migrations in coordination with live deployments.

Distributed Tasks: Build and tune background workers and scheduled jobs (ingestion, sync, aggregation)—focusing on failure modes, retries, and deep observability.

Polyglot Contributions: Support Python-based services for streaming, automation, or ML-adjacent pipelines (inference/training) alongside the core stack.

Systems Ops: Enhance our infrastructure practices, including environment discipline, health checks, and container-based deployment patterns.

What we’re looking for
Server-side TypeScript: Deep experience with Node.js; you should be comfortable owning API contracts from end to end.

Modern Frontend: Production-grade React and Next.js (App Router experience is a major plus).

Data Integrity: Solid SQL and PostgreSQL skills with a pragmatic approach to performance and correctness in high-stakes environments.

Asynchronous Logic: Experience running long-lived processes and worker-based systems, not just simple request/response APIs.

Tooling Versatility: Ability to leverage Python for specialized services or data tooling when the use case fits.

Operational Maturity: Clear communication, sound judgment on scope, and the ability to debug across a distributed architecture.

Nice to have
Security & Identity: Experience with OAuth, session security, and API protection tradeoffs.

Infrastructure: Experience with Docker or systemd-style multi-process layouts.

Applied ML: Exposure to ML workflows (training scripts, checkpoints, inference) within a production product.

Streaming Data: Background in high-volume data paths or real-time event streaming.