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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Python Engineer - AI Agents, Forecasting - **Company:** Addington - **Location:** UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Elastic Compute Cloud, Computer Programming, Databases, Statistical Hypothesis Testing, Python (Programming Language), Cloud Platform System, Large Language Models, Reliability of Systems, Backend, Scikit Learn, Kubernetes, Api Design, Data Pipelines - **Published:** August 22, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/senior-python-engineer-ai-agents-forecasting/44468825 ## About the Role 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 orchestrationStrong backend fundamentals including API design, async programming, and database modellingYou've built systems that had to work reliably at scale, not just pass a demoWorked at an early-stage startup or high-growth environment. You understand the pace.Built and shipped production systems, not just prototypesComfortable being the most senior engineer in the room, or the only oneYou 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 theoryML experience including random forests, regression models, scikit-learn, and PyTorchAWS 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 DevelopmentLLM Orchestration FrameworksDagster Pipeline OrchestrationBackend FundamentalsAWS Infrastructure ExperienceATS Optimization Keywords Hard Skills PythonAPI DesignAsync ProgrammingDatabase ModellingRandom ForestsRegression ModelsScikit-LearnPyTorchMathematicsStatisticsSoft Skills Holistic ThinkingResearch-Driven Problem SolvingLeadershipIndustry Keywords Financial MarketsAlgo-TradingPrediction Market PlatformsOpen-Source ContributionsTools & Technologies LangChainLangGraphDagsterAWS EC2AWS LambdaAWS RDS #J-18808-Ljbffr ## Related Videos - [Building a Multi-Agent Orchestration Engine That Actually Follows the Rules](https://www.wearedevelopers.com/videos/100159-building-a-multi-agent-orchestration-engine-that-actually-follows-the-rules) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [On a Secret Mission: Developing AI Agents](https://www.wearedevelopers.com/videos/1510-on-a-secret-mission-developing-ai-agents) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)