You'll architect and build the core infrastructure of the Numinous platform. This is the backbone that allows autonomous AI agents to ingest data, reason, compete, and forecast.
Designing and building the agent orchestration pipeline that allows AI forecasters to ingest data, reason, and produce predictions.
Building and optimising the signal pipeline that feeds real-world data into forecasting models.
Experimenting with different forecasting architectures to find optimal approaches for linking targets to signals.
Writing production-grade Python that handles complexity at scale, not scripts that work in a notebook.
Contributing to technical strategy alongside the founders. You'll have a voice in what gets built and why.
Evaluating and vetting technical candidates as the engineering team grows.

Requirements

5+ years building production-grade Python backends. You know the internals, not just the syntax.
Hands-on experience with LLM orchestration frameworks such as LangChain or LangGraph (agent memory, tool calling, state management)
Dagster in production (assets, sensors, partitions) or equivalent pipeline orchestration
Strong backend fundamentals including API design, async programming, and database modelling
You've built systems that had to work reliably at scale, not just pass a demo
Worked at an early-stage startup or high-growth environment. You understand the pace.
Built and shipped production systems, not just prototypes
Comfortable being the most senior engineer in the room, or the only one

Benefits

Equity: Competitive for the right candidate

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonLLM orchestration frameworksLangChainLangGraphDagsterAPI designasync programmingdatabase modellingproduction-grade systemsforecasting architectures

Soft Skills

technical strategy contributionevaluating technical candidatesleadershipcommunicationadaptability