Jobs via eFinancialCareers
Lead Quant Systems Engineer -- Backtesting & Data - Quant Genie AI
Jobs via eFinancialCareers, Chicago, Illinois, United States, 60290
Lead Quant Systems Engineer – Backtesting & Data (Quant Genie AI)
Location:
United States (Remote) Employment:
Full-Time Seniority:
Founding Engineer / Technical Lead
QuantGenie.ai is a no‑code platform that lets anyone build, backtest, and deploy trading strategies using natural language.
In this high‑impact founding role you will drive the core simulation and data platform, owning the backtesting engine and the underlying time‑series infrastructure.
You will be hands‑on for about 70% of your time while leading a small engineering team and shaping the company’s engineering culture.
Responsibilities
Lead architecture and development of the core backtesting engine
Own design of tick‑level precision event modeling, bar‑based iteration, deterministic execution logic, slippage/spread modeling, and order‑state transitions
Engineer multi‑asset, multi‑strategy portfolio simulation with reproducibility, latency reduction, and correctness guarantees
Scale heavy workloads through parallelization, caching, and batching
Architect ingestion, normalization, and storage pipelines for tick, OHLCV, and derived features
Develop indexing, caching, and retrieval patterns optimized for simulation workloads
Build pipelines to compute and version indicators at scale and align intraday multi‑symbol data
Define the technical roadmap, set engineering standards, and guide backend and data engineers
Collaborate with product and pricing‑action SMEs to ensure semantic correctness of signals, indicators, and strategy constructs
Qualifications Required Technical Must‑Haves
End‑to‑end experience building a backtesting engine (not just using 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 with focus on systems architecture and performance engineering
Ability to design scalable data pipelines and simulation architectures
Capability to lead engineers while remaining hands‑on
Domain Must‑Haves
Strong understanding of markets, strategy development workflows, indicators, and signal construction
Comfort working with quants, NLP/LLM engineers, and product stakeholders
Ability to reason deeply about correctness, edge‑cases, and simulation fidelity
Leadership Must‑Haves
Establishment of engineering processes from scratch
Making clean architectural decisions early and avoiding over‑engineering
Thriving in early‑stage ambiguity while maintaining rigor
Bonus (Not Required)
Experience scaling parallel backtests or distributed compute
Experience with GPU acceleration or optimizers such as Numba/Polars/Rust/Cython
Familiarity with DSL/AST/strategy‑language design
Prior fintech/quant/startup experience
Compensation
Competitive salary
Meaningful equity
Direct influence over architecture, team, and long‑term product direction
#J-18808-Ljbffr
United States (Remote) Employment:
Full-Time Seniority:
Founding Engineer / Technical Lead
QuantGenie.ai is a no‑code platform that lets anyone build, backtest, and deploy trading strategies using natural language.
In this high‑impact founding role you will drive the core simulation and data platform, owning the backtesting engine and the underlying time‑series infrastructure.
You will be hands‑on for about 70% of your time while leading a small engineering team and shaping the company’s engineering culture.
Responsibilities
Lead architecture and development of the core backtesting engine
Own design of tick‑level precision event modeling, bar‑based iteration, deterministic execution logic, slippage/spread modeling, and order‑state transitions
Engineer multi‑asset, multi‑strategy portfolio simulation with reproducibility, latency reduction, and correctness guarantees
Scale heavy workloads through parallelization, caching, and batching
Architect ingestion, normalization, and storage pipelines for tick, OHLCV, and derived features
Develop indexing, caching, and retrieval patterns optimized for simulation workloads
Build pipelines to compute and version indicators at scale and align intraday multi‑symbol data
Define the technical roadmap, set engineering standards, and guide backend and data engineers
Collaborate with product and pricing‑action SMEs to ensure semantic correctness of signals, indicators, and strategy constructs
Qualifications Required Technical Must‑Haves
End‑to‑end experience building a backtesting engine (not just using 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 with focus on systems architecture and performance engineering
Ability to design scalable data pipelines and simulation architectures
Capability to lead engineers while remaining hands‑on
Domain Must‑Haves
Strong understanding of markets, strategy development workflows, indicators, and signal construction
Comfort working with quants, NLP/LLM engineers, and product stakeholders
Ability to reason deeply about correctness, edge‑cases, and simulation fidelity
Leadership Must‑Haves
Establishment of engineering processes from scratch
Making clean architectural decisions early and avoiding over‑engineering
Thriving in early‑stage ambiguity while maintaining rigor
Bonus (Not Required)
Experience scaling parallel backtests or distributed compute
Experience with GPU acceleration or optimizers such as Numba/Polars/Rust/Cython
Familiarity with DSL/AST/strategy‑language design
Prior fintech/quant/startup experience
Compensation
Competitive salary
Meaningful equity
Direct influence over architecture, team, and long‑term product direction
#J-18808-Ljbffr