Jobs via eFinancialCareers · 22 hours ago
Lead Quant Systems Engineer -- Backtesting & Data - Quant Genie AI
United States
Full-time
Remote
Lead/StaffQuantGenie.ai is a no-code platform that enables users to build, backtest, and deploy trading strategies using natural language. The Lead Quant Systems Engineer will lead the architecture and development of the core simulation and data platform while managing a small engineering team, focusing on building a backtesting engine and ensuring the correctness and efficiency of trading systems.
Financial Services
Responsibilities
You will own the design and evolution of our engine, including:
Tick-level precision event modeling
Bar-based iteration across multiple timeframes (intraday + higher TFs)
Deterministic execution logic, slippage/spread modeling, and order-state transitions
Multi-asset, multi-strategy portfolio simulation
Reproducibility, latency reduction, and correctness guarantees
Scaling approaches for heavy workloads (parallelization, caching, batching)
You will architect or supervise the architecture of:
Ingestion + normalization for tick, OHLCV, volume, and derived features
Efficient storage formats for large datasets
Indexing, caching, and retrieval patterns optimized for simulation workloads
Pipelines to compute and version indicators at scale
Intraday multi-symbol data alignment
Define the technical roadmap and engineering standards
Lead backend and data engineers to deliver high-quality, reliable systems
Guide design around performance, determinism, and debuggability
Shape the infra supporting NL → SDL → execution workflows
Collaborate with product and our price-action SME to ensure semantic correctness of signals, indicators, and strategy constructs
Qualification
Required
You've built a backtesting engine end-to-end (not just used one)
Deep understanding of trading-system mechanics, order state machines, execution modeling, and determinism
Strong experience with tick data, multi-timeframe intraday data, and high-volume time-series engineering
Python expertise — but more importantly, systems architecture and performance engineering expertise
Ability to design scalable data pipelines and simulation architectures
Ability to lead engineers while staying hands-on
Strong understanding of markets, strategy development workflows, indicators, and signal construction
Comfort working with quants, NLP/LLM engineers, and product stakeholders
Ability to reason about correctness, edge-cases, and simulation fidelity at a deep level
Can establish engineering processes from scratch
Makes clean architectural decisions early (and knows when not to over-engineer)
Thrives in early-stage ambiguity while maintaining rigor
Preferred
Experience scaling parallel backtests or distributed compute
Experience with GPU acceleration or optimizers like Numba/Polars/Rust/Cython
Familiarity with DSL/AST/strategy-language design
NinjaTrader, MT5, IBKR, or exchange-style execution modeling
Prior fintech/quant/startup experience
Benefits
Competitive salary
Meaningful equity
Company
Jobs via eFinancialCareers
The space to inspire and grow exceptional careers in financial services and tech.
Founded in 2000
201-500 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase