Algorithmic Trading Developer

Algorithmic Trading Developer(Execution, Risk, ML & Infrastructure)Level: Mid-level (3–5 years hands-on algorithmic/quantitative trading experience)Engagement: Full-time, in-houseMarkets Covered: Forex (MT4/MT5)

• Crypto exchange APIs
• Equities and F&O broker APIsReports To: Head of Algo Trading / FounderAbout AJAlgo AJALGO runs a portfolio of automated trading bots across Forex (MT4/MT5), crypto exchanges, and equity/F&O broker APIs. We build and operate systems that don't just generate trading signals, they execute them reliably, enforce risk discipline in code, and stay resilient around the clock. Our focus is on building robust, well-monitored infrastructure where every trade is accounted for and every risk limit is enforced automatically, not manually. We're a small, hands-on team where engineering rigor and calibrated scepticism matter as much as trading performance.About the RoleWe run a portfolio of automated trading bots across Forex (MT4/MT5), crypto exchanges, and equity/F&O broker APIs. The bots generate the signals; this role owns everything that happens after the signal, and everything the bots depend on to stay alive.What You'll OwnSignal Execution & MonitoringOwn the order pipeline end to end: signal, risk checks, order routed, fill confirmed, position tracked, loggedBuild and maintain a live monitoring dashboard (positions, P&L, exposure, latency, bot heartbeat)Handle rejected orders, partial fills, requotes, slippage, disconnects, and stale prices explicitlyRun daily reconciliation between bot-held positions and broker/exchange recordsMaintain a real-time alerting system with clear severity levelsMoney Management & Risk ControlImplement position sizing in code: fixed-fractional risk, volatility-adjusted lots, hard caps per symbol/strategy/accountEnforce daily/weekly loss limits, drawdown stops, and margin safeguardsTrack correlated exposure across bots and instrumentsGuarantee every position carries a stop loss, including after restartsProduce daily risk reportsMachine Learning on Trade HistoryBuild clean, versioned datasets from historical trades and market contextEngineer features while avoiding look-ahead biasTrain models for signal filtering and position sizing (meta-labelling approach)Validate using walk-forward and purged/embargoed cross-validationDeploy with shadow, small allocation, then full allocation, with rollback plansMonitor for model drift and define retraining triggersServer & Trading Terminal OperationsProvision and maintain Linux VPS (bots) and Windows VPS (MT4/MT5 terminals) near broker/exchange serversRun services under process supervision for automatic recoverySet up uptime, resource, and heartbeat monitoring with alerts; maintain exact NTP syncHarden access: key-based SSH, vaulted secrets, least-privilege API keysMaintain and test backups of trade database, config, and model artefactsDocument failover and disaster-recovery runbooksMust-Have Skills & Experience3–5 years building/operating automated trading systems that traded real money (not just backtests)Strong Python (pandas, NumPy, asyncio, REST/WebSocket clients); Git, structured logging, tests for money-touching codeWorking knowledge of MQL4/MQL5 or driving MT5 from Python; understands magic numbers, order lifecycle, hedging vs. nettingExperience integrating at least one crypto exchange API and one broker API; rate limits, idempotent order IDs, reconciliationFluent in market mechanics: spread, slippage, swap/funding, margin, leverage, partial fills, rolloverCan compute correct lot size from equity, stop distance, tick value, and risk % on the spotPractical ML experience (scikit-learn, XGBoost/LightGBM); understands overfitting, leakage, and why standard k-fold fails for time-seriesConfident on Linux (SSH, systemd, cron); comfortable administering Windows VPS for MT terminalsSQL competence with trade/time-series data (PostgreSQL/TimescaleDB/SQLite)Conservative temperament: defaults to halting and escalating rather than improvising with live capitalGood to HaveExperience at a prop firm, hedge fund, HFT desk, or funded-trader programmeDocker, CI/CD, infrastructure-as-code (Ansible/Terraform), Prometheus + GrafanaC++/C# for latency-sensitive components; FIX protocolFamiliarity with triple-barrier labelling, meta-labelling, purged K-fold with embargoOptions/F&O knowledge: Greeks, SPAN margin, expiry-day behaviourPublic repository, research write-up, or verifiable track recordShare Your Resumeat: admin@ajems.com.