BHFT

• Advisory compliance — primary owner, all regions • Real-time trading guidance across all asset classes and venues • Building and maintaining a pre-cleared rules framework for recurring desk queries • Advising development, trading, and operations teams on building and maintaining compliant tools and processes • Building out a comprehensive algo trading governance framework covering the full lifecycle — pre-deployment approvals, ongoing monitoring, change management, business continuity, information security, and annual review • New market and product approvals • Core compliance — oversee two Compliance Officers responsible for: • Trade surveillance across all venues • Regulatory and exchange affairs — filings, registrations, regulator and exchange inquiries, client/due-diligence reviews, FCM interface • Policies and training — maintaining the policy framework and running the training program across all regions • AML and sanctions — screening vendors and counterparties (brokers, FCMs) • Leadership Supervising and developing two Compliance Officers • Representing compliance in cross-functional discussions with risk, development, and front office • Escalation point for non-routine compliance matters

• Own end-to-end options strategy research: hypothesis → data → modeling → backtesting → production → live monitoring and iteration • Work on Relative Value, Statistical Arbitrage, and Spread Trading strategies specific to the options universe (the stack above) • Build and own the volatility fitter the signals sit on – calibrating arbitrage-free, temporally stable surfaces (SVI/SSVI or a proposed alternative) on realistic data (wide bid/ask, missing strikes, gaps, latency), with attention to residual noise near expiry / illiquid strikes / events • Translate strategy output into execution – routing a target delta-order across option legs to minimize Greek risk, with inventory-aware quoting that shifts price/size against live vega/gamma/skew, and awareness of options microstructure (spreads, queue, adverse selection, latency) • Build and maintain mid-frequency (MFT), fully automated strategies with a strong live-performance focus • Track record of deploying fully automated strategies with Sharpe > 2 (or demonstrable equivalent risk-adjusted performance) • Design robust signal research pipelines (feature engineering, labeling, validation, regime analysis) • Develop realistic backtests and live-simulation frameworks accounting for slippage, spreads, latency, partial fills, and market impact • Work in tight feedback loops with trading and execution to improve PnL, robustness, and risk-adjusted performance • Debug and tune research outputs under live conditions: data issues, execution artifacts, microstructure noise, and changing market regimes

Role Description We are building a proprietary HFT trading team focused on Indian markets. Our infrastructure provides direct NSE connectivity with low-latency market data and execution. Backtesting runs on high-quality historical NSE data. We are looking for an experienced HFT Trader who is comfortable operating in a growing environment and wants to contribute to strategy development while working closely with the engineering team. - Develop, backtest, and deploy HFT strategies on NSE Options (primary focus), with a roadmap to expand into additional NSE instruments - Collaborate with the engineering team on execution quality, latency optimization, and order routing - Participate in platform calibration and performance improvements as strategies scale - Build a strategy library that can grow with the platform Qualifications - Hands-on experience developing and deploying strategies in the microsecond-to-millisecond range - Strong understanding of NSE market microstructure – options pricing, order book dynamics, flow toxicity - Solid grasp of execution best practices: order types, queue positioning, adverse selection management - Strong programming skills in C++ or Rust are required. You will be expected to independently implement, maintain, and optimize production trading strategies and execution logic - Comfortable independently developing production trading robots on top of an existing trading platform - Clear thinking on pre-trade risk: position limits, order rate limits, kill-switch requirements – and the latency cost you're willing to pay for them - Rigorous approach to backtest validation: you know the first things to check before trusting a result, and you understand the impact of market data timestamp accuracy on strategy performance - Proactive, communicates openly, thrives in a collaborative environment Company Description BHFT is a proprietary algorithmic trading firm. Our team manages the full trading cycle, from software development to creating and coding strategies and algorithms. Our trading operations cover key exchanges. The firm trades across a broad range of asset classes, including equities, equity derivatives, options, commodity futures, rates futures, etc. We employ a diverse and growing array of algorithmic trading strategies, utilizing both HFT and MFT approaches. We’ve got a team of 200+ professionals, with a strong emphasis on technology. Our employees are located all around the world, from the United States to Hong Kong. Although we maintain office spaces, we currently operate as a 100% remote organization.

• Develop and evaluate systematic equity trading opportunities. • Collaborate with research and technology teams on strategy deployment. • Identify new sources of alpha across US equities. • Drive improvements in execution and portfolio construction. • Participate in the design of trading infrastructure and analytics.

• Run and maintain the firm’s VaR and risk systems daily. • Monitor trading exposures in real time against the firm’s risk limits. • Reconcile daily margin requirements against FCM statements and calls. • Execute daily stress tests and scenario analyses. • Identify and investigate outliers, data issues, or unexpected spikes in VaR or risk metrics. • Maintain a working understanding of daily P&L by strategy. • Run the daily liquidity reserve model to assess bid/ask costs for exiting positions. • Prepare and distribute clear daily risk reports to the senior management.

• Capture & Ingestion: Own the full capture path from wire to lake • Build batch + stream pipelines (Airflow, Spark, dbt) for tick and reference data • Own L2/L3 order-book reconstruction with gap handling • Storage & Modeling: Own the Iceberg-over-S3 lakehouse • Drive storage cost optimisation via compaction, tiering, and snapshot expiry • Tooling & Libraries: Build libraries for schema management, data contracts, validation, and lineage • Reliability & Observability: Embed monitoring, alerting, SLAs/SLOs, and CI/CD across capture and pipeline layers on Kubernetes • Collaboration: Partner with Quant Research, Data Science, Backend, and DevOps to translate requirements into platform capabilities

• Capture & Ingestion. Own the full capture path from wire to lake: decode and normalize raw exchange feeds (pcap, multicast UDP / ITCH / FIX) and vendor sources (OneTick, Refinitiv, Bloomberg, ICE) into a unified canonical model with nanosecond timestamps. Build batch + stream pipelines (Airflow, Spark, dbt) for tick and reference data. Own L2/L3 order-book reconstruction with gap handling. Provide Python and Rust producer SDKs for internal feed handlers. • Storage & Modeling — Apache Iceberg. Own the Iceberg-over-S3 lakehouse: design partitioning, sort orders, and row-group layout for fast scans; manage schema evolution, snapshots, time travel, compaction, and TTL. Maintain reference data as slowly-changing tables with point-in-time correctness for backtests. Drive storage cost optimisation via compaction, tiering, and snapshot expiry. • Tooling & Libraries. Build libraries for schema management, data contracts, validation, and lineage on top of the Iceberg catalog. Develop shared access services (Spark + Polars) so Research, backtesting, and trading share one normalized data layer, including gap detection and pcap-vs-lake reconciliation. • Reliability & Observability. Embed monitoring, alerting, SLAs/SLOs, and CI/CD across capture and pipeline layers on Kubernetes (EKS). Own data-quality dashboards and incident runbooks for the capture fleet. • Collaboration. Partner with Quant Research, Data Science, Backend, and DevOps to translate requirements into platform capabilities and champion market-data engineering best practices.

• Be the primary interface with external stakeholders — auditors, tax authorities, banks, and regulators • Own the preparation of statutory financial statements under IFRS • Manage external audit processes across multiple jurisdictions • Ensure tax compliance across the UAE, USA, India, China, and other key markets • Provide seamless cover to your Finance Manager peer on management accounting activities

• Own the annual budget and rolling forecasts across all group entities • Lead monthly variance reviews with budget holders • Review invoices and purchase contracts against approved budgets • Monitor committed vs. available budget in real time • Lead the Finance stream of our ERP project • Produce monthly, quarterly, and annual management accounts with analytical commentary • Provide interchangeable cover to the FM – Financial Reporting & Audit on statutory accounts

• Risk System Operation: Run and maintain the firm’s VaR and risk systems daily. Ensure all positions and strategies are accurately captured, priced, and reflected in the risk engine. • Intraday Limit Monitoring: Monitor trading exposures in real time against the firm’s risk limits (position size, margin, and concentration). Identify and escalate potential breaches promptly. • Margin Tool Operation: Reconcile daily margin requirements against FCM statements and calls. Run what-if scenarios across exchanges and FCMs to optimize margin usage, reduce capital requirements, and identify efficiencies. • Stress Testing: Execute daily stress tests and scenario analyses. • Anomaly Detection & Tool Ownership: Identify and investigate outliers, data issues, or unexpected spikes in VaR or risk metrics. Own the resolution of technical or pricing problems within the risk and margin systems and escalate persistent issues. • Produce daily P&L reports broken down by strategy. Provide clear attribution and trend analysis (daily, week-to-date, and month-to-date performance). Deliver factual explanations of P&L fluctuations, linking results to market events, strategy behavior, and execution factors. • Run the daily liquidity reserve model to assess bid/ask costs for exiting positions. Apply liquidity reserves to valuations to produce realistic P&L figures. • Prepare and distribute clear daily risk reports to the Head of Risk and senior management, covering VaR, key exposures, margin utilization, and limit status. Communicate daily P&L results, attribution details, and performance trends (daily/WTD/MTD) to traders and senior management. Explain the impact of liquidity reserves on P&L and present both raw and reserve-adjusted P&L figures. Conduct regular reviews with traders on risk positioning, proactively flag elevated risks or limit concerns, and discuss stress test results and margin optimization opportunities.