Senior Python Engineer – AI Agents, Forecasting

The Generalist Co.

Senior Python Engineer architecting the Numinous platform infrastructure for AI agents. Involves backend architecture, building data pipelines and complex systems for forecasting models.

Posted 7/29/2026full-timeLondon • 🇬🇧 United KingdomSenior💰 £80,000 - £120,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building production-grade Python backends and orchestrating complex data pipelines, with a strong focus on system reliability and scalability. Possesses a quantitative background and experience in financial markets, enabling effective problem-solving and strategic contributions to technical direction.

Highest-signal resume keywords

Production-Grade Python DevelopmentLLM Orchestration FrameworksDagster Pipeline OrchestrationBackend FundamentalsAWS Infrastructure Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonAPI DesignAsync ProgrammingDatabase ModellingRandom ForestsRegression ModelsScikit-LearnPyTorchMathematicsStatistics

Soft Skills

Holistic ThinkingResearch-Driven Problem SolvingLeadership

Tools & Technologies

LangChainLangGraphDagsterAWS EC2AWS LambdaAWS RDS

Industry Keywords

Financial MarketsAlgo-TradingPrediction Market PlatformsOpen-Source Contributions

Tech Stack

Tools & technologies

AWSCloudEC2PythonPyTorchScikit-Learn

About the role

Key responsibilities & impact

Unifying the different parts of the stack. The network, signal layers, and forecasting architectures need to work together as one coherent system.
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

What you’ll need

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
You think holistically about systems. You see how your work connects to every other part of the product without being told.
Research-driven approach to problem solving. You test hypotheses, not just ship features.
Experience in financial markets, algo-trading, or prediction market platforms (Polymarket, Manifold, etc.)
Quantitative background in maths, statistics, or probability theory
ML experience including random forests, regression models, scikit-learn, and PyTorch
AWS infrastructure experience deploying containerised applications and managing cloud environments (EC2, Lambda, RDS)
Open-source contributions to AI or crypto projects.

Benefits

Comp & perks

Equity: Competitive for the right candidate