Remote Backend Jobs

We re assembling a core engineering strike team of ambitious builders. This isn 0t a corporate job it 0s an opportunity for engineers who want to create, ship, and evangelize world-class software at speed. For this role we will consider contractor or permanent applications. Our products span multiple systems and use-cases, and we re looking for a full-stack engineer who leans strongly toward backend and systems work: building the foundations that keep things fast, reliable, scalable, and real-time. You 0ll help shape how we architect and evolve services, messaging, data, and APIs across our ecosystem while contributing across the stack when needed. Just as important: you 0ll help us push an AI-first engineering culture, where applied AI tooling meaningfully accelerates delivery and improves quality.

Responsibilities

• Design, build, and maintain systems across our product ecosystem with clean, scalable code.
• Improve and evolve backend foundations: service architecture, messaging/event flows, data reliability, and real-time delivery.
• Participate in system design, architecture discussions, and scaling strategies 0 0 0keeping things simple, robust, and observable.
• Move fast: prototype, iterate, and ship improvements in days, not months 0then harden what works.
• Use and evangelize AI-assisted workflows across the team to increase shipping velocity and quality.
• Own work end-to-end: ideation 0 execution 0 deployment 0 monitoring.
• Mentor peers in best practices, especially around AI-assisted development and building operable systems.

Candidate Profile

• Experience: ~5 years professional engineering experience with a strong portfolio of shipped projects (startups, open source, or commercial).
• Mindset: Hungry, ambitious, comfortable wearing multiple hats in a small team. Bias for action. Obsessed with outcomes, not process.
• Systems Focus: You 0ve built and operated backend systems where correctness, performance, and reliability matter. You enjoy making things faster, safer, and easier to run.
• AI Evangelist: You already use AI tools daily to accelerate coding, refactoring, debugging, testing, and architecture work 0and you can explain (concretely) how it improves your output.
• Cultural Fit: Builder mentality. Thrive in chaos. Strong ownership. Low ego, high standards.

Technical Stack

We don t expect you to tick every box, we care about strong fundamentals and being effective in a small team.

Core

• Backend / Systems Engineering: Experience building performance-sensitive services and real-time systems: concurrency, messaging/event flows, state management, and designing for reliability.
• Systems-level languages (examples): Not tied to one language, but you 0ve used 0systems / performance-oriented 0languages in production (e.g., Go, Rust, C#, C++ or similar) and are comfortable working close to the metal when needed.
• Architecture: You can design how components fit together: service boundaries, communication patterns, data flow, and pragmatic scaling approaches.
• Applied AI (core): Practical experience using AI tooling in day-to-day engineering (coding, debugging, automation, data/feature work, and system design).

Data / Backend

• Databases: Strong with Postgres (plus real production experience: migrations, indexing, performance, safe changes). Familiarity with Redis and caching patterns.
• APIs & Real-time: Designing and operating APIs and real-time delivery (e.g., WebSockets or equivalent), and building systems that can handle spikes and sustained load.

Helpful

• DevOps familiarity: Comfortable collaborating on deployments, CI/CD, and cloud infrastructure decisions not necessarily the dedicated DevOps owner.
• Frontend contribution: Able to contribute when needed (we use modern web stacks), but this role is primarily backend/systems.

Bonus

• Web3 experience (Solidity/EVM/Sui/Solana).
• Deep experience with real-time systems, trading-style systems, or high-throughput event pipelines.
• Experience building AI-powered features or integrations beyond 0using AI tools 0 (e.g., production LLM features, evals, RAG, agentic workflows).