Lead Research Platform Engineer
⚲ Amsterdam (relocation possible) / Remote
About the Role
As a Lead Research Platform Engineer, you will own the platform that connects quantitative research with production trading — from architecture and hands-on development to the team building it. You will build the platform from zero, enabling researchers to move from hypothesis to production without rewriting their work. The core constraint is research throughput: how quickly and reliably we can generate, test, evaluate, and deploy new ideas. This is a hands-on leadership role. You will set the technical direction, write code, and build a small platform team, while gradually pushing ownership down rather than becoming its bottleneck. The platform will be designed from day one for an increasingly autonomous research process, where AI agents can access data, run experiments, evaluate results, and promote or discard ideas through programmatic and measurable interfaces.
You will work on
Own the research platform end to end: architecture, delivery, adoption, andimpact
Build and lead a small platform team, including hiring, mentoring, and defining ownership
Build a seamless path from research to production with reproducible environments and deployment workflows
Define APIs, artifact formats, data contracts, and promotion gates between research and production
Build a unified data layer for market and alternative data
Develop backtesting and simulation infrastructure, including measuring deviation between backtested and live results
Design deterministic, machine-readable interfaces for researchers and AI agents
Work directly with researchers to identify bottlenecks and turn them into platformcapabilities
Make pragmatic build-vs-buy and prioritization decisions
About the Team
We are building a research lab first — and a proprietary investment fund around it. Our core belief is that long-term trading edge comes from the ability to generate, test, and compound research insights faster and more rigorously than the market. Our goal is to tightly integrate execution, research, and infrastructure into a single
You might thrive in this role if you have
Experience leading a small platform, infrastructure, developer tooling, or research infrastructure team while remaining hands-on
Experience building systems or teams from scratch and operating with significant ownership
Strong systems programming skills in Go and/or Rust, with a deep understanding of concurrency, memory, runtimes, and performance
Experience designing complex systems with clear abstractions and interfaces
Experience building platforms or infrastructure used by other engineers
Experience with data and distributed systems; Kafka, Postgres, or ClickHouse is a plus
Strong product judgment around adoption, correctness, reproducibility, and build- vs-buy decisions
Ability to set technical direction without becoming the team's bottleneck
Lead Research Platform Engineer
⚲ Amsterdam (relocation possible) / Remote
About the Role
As a Lead Research Platform Engineer, you will own the platform that connects quantitative research with production trading — from architecture and hands-on development to the team building it. You will build the platform from zero, enabling researchers to move from hypothesis to production without rewriting their work. The core constraint is research throughput: how quickly and reliably we can generate, test, evaluate, and deploy new ideas. This is a hands-on leadership role. You will set the technical direction, write code, and build a small platform team, while gradually pushing ownership down rather than becoming its bottleneck. The platform will be designed from day one for an increasingly autonomous research process, where AI agents can access data, run experiments, evaluate results, and promote or discard ideas through programmatic and measurable interfaces.
You will work on
Own the research platform end to end: architecture, delivery, adoption, andimpact
Build and lead a small platform team, including hiring, mentoring, and defining ownership
Build a seamless path from research to production with reproducible environments and deployment workflows
Define APIs, artifact formats, data contracts, and promotion gates between research and production
Build a unified data layer for market and alternative data
Develop backtesting and simulation infrastructure, including measuring deviation between backtested and live results
Design deterministic, machine-readable interfaces for researchers and AI agents
Work directly with researchers to identify bottlenecks and turn them into platformcapabilities
Make pragmatic build-vs-buy and prioritization decisions
About the Team
We are building a research lab first — and a proprietary investment fund around it. Our core belief is that long-term trading edge comes from the ability to generate, test, and compound research insights faster and more rigorously than the market. Our goal is to tightly integrate execution, research, and infrastructure into a single
You might thrive in this role if you have
Experience leading a small platform, infrastructure, developer tooling, or research infrastructure team while remaining hands-on
Experience building systems or teams from scratch and operating with significant ownership
Strong systems programming skills in Go and/or Rust, with a deep understanding of concurrency, memory, runtimes, and performance
Experience designing complex systems with clear abstractions and interfaces
Experience building platforms or infrastructure used by other engineers
Experience with data and distributed systems; Kafka, Postgres, or ClickHouse is a plus
Strong product judgment around adoption, correctness, reproducibility, and build- vs-buy decisions
Ability to set technical direction without becoming the team's bottleneck
Lead Research Platform Engineer
⚲ Amsterdam (relocation possible) / Remote
About the Role
As a Lead Research Platform Engineer, you will own the platform that connects quantitative research with production trading — from architecture and hands-on development to the team building it. You will build the platform from zero, enabling researchers to move from hypothesis to production without rewriting their work. The core constraint is research throughput: how quickly and reliably we can generate, test, evaluate, and deploy new ideas. This is a hands-on leadership role. You will set the technical direction, write code, and build a small platform team, while gradually pushing ownership down rather than becoming its bottleneck. The platform will be designed from day one for an increasingly autonomous research process, where AI agents can access data, run experiments, evaluate results, and promote or discard ideas through programmatic and measurable interfaces.
You will work on
Own the research platform end to end: architecture, delivery, adoption, andimpact
Build and lead a small platform team, including hiring, mentoring, and defining ownership
Build a seamless path from research to production with reproducible environments and deployment workflows
Define APIs, artifact formats, data contracts, and promotion gates between research and production
Build a unified data layer for market and alternative data
Develop backtesting and simulation infrastructure, including measuring deviation between backtested and live results
Design deterministic, machine-readable interfaces for researchers and AI agents
Work directly with researchers to identify bottlenecks and turn them into platformcapabilities
Make pragmatic build-vs-buy and prioritization decisions
About the Team
We are building a research lab first — and a proprietary investment fund around it. Our core belief is that long-term trading edge comes from the ability to generate, test, and compound research insights faster and more rigorously than the market. Our goal is to tightly integrate execution, research, and infrastructure into a single
You might thrive in this role if you have
Experience leading a small platform, infrastructure, developer tooling, or research infrastructure team while remaining hands-on
Experience building systems or teams from scratch and operating with significant ownership
Strong systems programming skills in Go and/or Rust, with a deep understanding of concurrency, memory, runtimes, and performance
Experience designing complex systems with clear abstractions and interfaces
Experience building platforms or infrastructure used by other engineers
Experience with data and distributed systems; Kafka, Postgres, or ClickHouse is a plus
Strong product judgment around adoption, correctness, reproducibility, and build- vs-buy decisions
Ability to set technical direction without becoming the team's bottleneck
