Experienced CTO-level Rust engineer with 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.

Tasks

• 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 TimescaleDB/PostgreSQL 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

Requirements

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 TimescaleDB/PostgreSQL; 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: FumaDocs 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

Benefits

• 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 apply if this isnt for you
• You will collaborate with an elite group of engineersamong the strongest youre likely to have worked with. All of our core developers are driven by pure intrinsic motivation and have spent years working day and night to reach this level
• Work on a high-performance production-grade trading platform covering the full stack of the engine from low-latency execution to data optimization and infrastructure. We value strong generalists who can reason across systems and effectively leverage modern AI tooling
• Risk-free probation period for both sides (part-time) ideal to test long-term fit while keeping your current job (1020h/week over 6 months)
• International remote-first culture

We have a very streamlined hiring process:

• Stage 01 Cover Letter (Skill Self-Assessment)
  Use the cover letter to explain why you are the right candidate for this role.
  Additionally assess your skill level in each area listed above and briefly justify your rating with concrete experience or examples
• Stage 02 Interview (2 hours)
  A deep wide-ranging (mainly technical) conversation no LeetCode nonsense no live coding.
  This is a real discussion between engineers. We will explore all areas listed above both broadly and in depth to understand how you think design and reason at scale.
  All questions are based on real problems and recent developments in our engine no artificial data-structure puzzles or interview-theater questions
• Stage 03 Probation Period (6 months part-time)
  A six-month trial collaboration to ensure a strong mutual fit.
  You will already work on real systems and contribute meaningfully. We will also meet in person during this phase. Compensation during this period is already structured as a reduced but meaningful profit share.
• Stage 04 Long-Term Collaboration Offer
  If the fit is right on both sides we will offer you a long-term collaboration with a very competitive compensation package (Profit-Share VSOP)