Senior Python Engineer – AI Agents, Forecasting

Jobtailor

Greater London

On-site

GBP 120,000 - 180,000

Full time

14 days+

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Job summary

Jobtailor is seeking an experienced backend engineer to unify the stack for AI forecasting at scale in London. You will connect the network, signal layers, and forecasting architectures into one coherent system, shipping production-grade Python that runs in real time rather than notebooks.

You will own the agent orchestration and signal pipelines, work closely with founders, and help shape technical direction.

Qualifications

5+ years building production-grade Python backends.
Hands-on with LangChain or LangGraph for orchestration.
Dagster in production or equivalent pipeline tooling.
Strong API design, async programming, and DB modelling.
Experience at startups/high-growth environments.
Senior engineer capable of leading technically.
Experience in finance/markets and ML models.

Responsibilities

Unify stack components: network, signals, and forecasting architectures.
Design and build the agent orchestration pipeline for AI forecasters.
Build and optimise the signal pipeline with real-world data.
Experiment with forecasting architectures to link targets and signals.
Write production-grade Python handling complexity at scale.
Contribute to technical strategy with founders.
Evaluate and vet engineering candidates as the team grows.

Skills

Production-Grade Python

LLM Orchestration

Dagster

Backend Fundamentals

AWS Infrastructure

Tools

LangChain

LangGraph

Dagster

AWS EC2

AWS Lambda

AWS RDS

Job description

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.

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