Experienced CTO-level Rust engineer quantitative background

This position is fundamentally different from most job roles.

We are a small group of entrepreneurs PhDs strong SW engineers full-time traders and international business people who enjoy the puzzles of the financial markets as peak intellectual entertainment
.

We are building a Rust-based agentic algorithmic trading platform targeting a highly lucrative niche
. The core system is already largely in place and we are now entering the monetization phase
.

Our compensation model is intentionally fair and uncommon
:
It isnt a founder takes all salary-only for all others setup.
Financial independence is a possible outcome of sustained team performance.

We are looking for
strong generalist engineering support to further enhance extend and maintain our algo-trading engine.

This is a once-in-a-lifetime opportunity for someone who truly understands our approach and wants to build something exceptional with a small high-caliber team where everyone owns a meaningful piece of the outcome.

• Full stack low-latency programming (Rust) - MUST HAVE: Build and maintain high-performance modular trading systems in Rust (backend bots optmization-system etc)
• Data engineering (Python): Develop TB-scale ETL pipelines using Python and Dagster for market data features backtests and optimizations
• Time-series data platforms: Design and optimize Timescale
  
  DB/Postgre
  
  SQL S3 based data warehouses (ingestion compression query performance)
• Infrastructure & Kubernetes: Operate IaC-driven infrastructure on Hetzner (Terraform) and production K3s clusters (Helm Kustomize)
• Monitoring & observability: Build dashboards and alerting for trading systems data quality latency and system health setup the TB-scale monitoring system behind it
• UI development: Create internal and end user-facing analytics dashboards React based user interfaces
• Practical algorithmic trading: Design trading signals trade management and large-scale strategy optimization frameworks
• Quantitative research & ML/AI: Develop evaluate and deploy quantitative models ML-based trading signals (feature engineering validation inference) and practical AI-agents
• Team collaboration: Work closely with traders and bot operators to monitor live systems investigate issues and improve performance

We search for an almost complete hand-on quantitative full stack developer who covers at least 5 of these 9 areas with expert knowledge. We do not care about formal degrees
; however they are often a strong indicator of capability
. We are equally open to being proven wrong.

Below is an overview which frameworks/technologies we use:

• Full stack low-latency programming (Rust) - MUST HAVE: SW best practices for Rust;
  Rust frameworks like Axum Tokio Rayon Serde tokio-postgres clorinde etc;
  Distributed low-latency coding with Rust;
  Contract-First API Development (OpenAPI)
• Data engineering (Python): Dagster with TB-scale data pipelines;
  Databento/Bybit/etc market data APIs; DB/TSDB migrations with Refinery
• Time-series data platforms: S3 Timescale
  
  DB/Postgre
  
  SQL; PGMQ messaging systems;
  High-performance compressed TB-scale ingestion pipelines for time-series data
• Infrastructure & Kubernetes: Hetzner (ARM/AMD nodes);
  Terraform; K3s Kubernetes clusters;
  Helm;
  Kustomize;
  Autoscaling nodes via K8sHCloud;
  Github actions CI/CD;
  ArgoCD; CNPG Traefik
• Monitoring & observability: Grafana stack (Grafana Mimir Loki Alloy k6); SRE knowledge
• UI development: Grafana charts;
  Volkov Business Suite for Grafana;
  Apache ECharts;
  React (JS/TS)
• Practical algorithmic trading: Practical knowledge about how to optimize trading stratgies and financial data;
  Solid knowledge of market microstructure and order-flowbased trading concepts eg bid/ask dynamics tick and lot structure order book behavior absorption and volume/delta imbalances;
  Quantower; C#/.net for trade execution adapters
• Quantitative research & ML/AI: Theoretical quant knowledge (eg Regime clustering mean reversion Stoch volatility models Brownian motion CVaR Monte Carlo sim Sharpe ratio etc); ML/AI:
  Deep learning architectures LLMs Reinforcement learning Hyperparameter optimization etc;
  Practical AI skills:
  Claude agents/skills n8n MindsDB
• Team collaboration: Strong team and communication skills in English (German is a plus);
  Tools:
  Fuma Docs MS Teams Jira

All of our core developers joined with real expert knowledge in at least 5 of these areas
. Rust is the only strict must-have
. Our expectation is that you bring the intrinsic motivation to become highly proficient across all of them over time
.

We do not believe in narrow specialization
. Instead we provide an environment with strong sparring partners deep technical discussions and real production responsibilityallowing you to grow rapidly. You will work alongside exceptional engineers quants and traders all pushing toward the same goal

• Due to the high
  potential
  payouts (up to $1M per year) and VSOP
  participation at the core company this role is fully profit-share based
  . We expect an entrepreneurial mindset from every team member. Dont…