Full Stack / AI Engineer

Role overviewAlgoChains is building the app store for automated investing — a validated strategy marketplace where traders subscribe to vetted bots, connect their own brokerage, and run automation without giving up custody. Four futures strategies trade live on real capital today; subscribers get institutional-style infrastructure (risk controls, telemetry, and AI automation) without being a hedge fund or broker.We need a Full Stack / AI Engineer to ship customer-facing products and the agent layers behind them — marketplace flows, Command Center dashboards, Supabase-backed metrics, and production AI integrations — AI agent APIs, multi-model signal validation, and intelligent model routing. This is a generalist builder role: you will touch UI, APIs, data pipelines, and LLM/agent features in the same week.What you'll work onMarketplace & web: Next.js/React surfaces, subscriber dashboards, Stripe checkout → entitlement → bot access (Command Center ops dashboard)Platform data: Supabase Postgres (RLS, migrations, live bot metrics, trade logs, billing tables); real-time performance cards and audit trailsLive trading ops: Python services connecting broker APIs (Tradovate, Alpaca), health monitoring, and safe-deploy workflows — strategy logic changes go through review, not pushed unilaterallyAI / agents: AI agent tooling (300+ production tools in our agent API layer), multi-model validation pipelines, semantic search, and cost-aware LLM routingML adjacent: Feature pipelines, model promotion gates, and shadow-mode AI models — you don't need to be a pure quant, but you should be comfortable calling real models and reading metricsWhat success looks like (first 90 days)Ship at least one end-to-end marketplace or Command Center feature (UI → API → Supabase → verified in staging)Harden one AI agent workflow used in ops (documented, smoke-tested)Ship to a system running real capital — we verify outputs against live broker state, not estimates, and deploy incrementallyQualificationsStrong TypeScript and Python in production (not tutorial-level)Built and shipped full-stack products (frontend + API + database), ideally at a startupComfortable with Postgres (schemas, migrations, basic RLS awareness)Experience integrating LLM APIs or agent frameworks (tools, prompts, evals, cost control)Ownership mindset: debug unfamiliar systems, write short docs, unblock yourselfClear written communication — we're remote-first and async-heavyNice to haveFintech, trading, or market-data exposure (brokers, websockets, fills — not FIX/HFT desk requirements)Next.js 15 / React 19, Supabase, Stripe subscriptionsMCP, FastAPI, or multi-agent orchestration experienceML ops basics: gradient-boosted model promotion, walk-forward/backtest disciplineSecurity-aware engineering (auth, secrets, least-privilege) — founder background is CTI/fintech securityWho thrives hereYou'd rather ship something real than prototype indefinitelyYou get uncomfortable when data is unverified — you check the sourceYou can context-switch between a UI feature and a Python service in the same sprintYou don't need a big team to move forward; you ask when blocked, figure out the rest