Senior Python Engineer – AI Agents, Forecasting

Responsibilities

• 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

• 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.

Core Competencies

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 Development
• LLM Orchestration Frameworks
• Dagster Pipeline Orchestration
• Backend Fundamentals
• AWS Infrastructure Experience

ATS Optimization Keywords

Hard Skills

• Python
• API Design
• Async Programming
• Database Modelling
• Random Forests
• Regression Models
• Scikit-Learn
• PyTorch
• Mathematics
• Statistics

Soft Skills

• Holistic Thinking
• Research-Driven Problem Solving
• Leadership

Industry Keywords

• Financial Markets
• Algo-Trading
• Prediction Market Platforms
• Open-Source Contributions

Tools & Technologies

• LangChain
• LangGraph
• Dagster
• AWS EC2
• AWS Lambda
• AWS RDS

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