Senior Backend Engineer with Python

At Behaviour Lab, we empower assets managers, private equity firms, insurance companies and executive boards across the globe to solve their trickiest problems. Our approach brings together analytics, research, algorithms, and science to help organizations continually improve their decision-making. Our vision is to transform how the £70 trillion active asset management industry makes investment decisions, through a smart decision-making platform built on behavioural science, advanced analytics and AI.

Overview of the Role

We are looking for an engineer who can be part of enabling us to do so. Ideally, you already have experience working with financial data or are eager to learn. You will build production backend components, contribute to writing customer data ingestion pipelines, and turn investment and behavioural methodologies into reliable, tested code.

You will spend most of your time writing and reviewing code, often through orchestrating AI coding agents and improving our AI harness. Some of your time will be allocated to working with our internal delivery team to make sure what we build gets used and delivers value to end users. Over time you will become a go-to expert on our Python analytics infrastructure and ETL pipelines.

You will thrive here if you are entrepreneurial, happy to wear whatever hat is needed, and curious about how investment decisions get made in large asset management organizations.

What You'll Do

• Write clean, effective and scalable code using Python and AWS services
• Work with financial data from a variety of client and third-party sources
• Develop back-end product components, databases and manage their deployments to AWS
• Translate methodologies (investment analytics, behavioural metrics, algorithms) into performant production code. Challenge the methodology where it doesn't hold up.
• Build and maintain ETL pipelines that ingest client and market data from APIs, SFTP and custom loaders.
• Support the front-end team in integrating user-facing features with backend APIs.
• Resolve bottlenecks in our SDLC to ensure timely delivery of features
• Orchestrate agentic development workflows and contribute to our AI harness

Requirements

• Degree in computer science, mathematics, physics, engineering, economics or finance
• Experience in working with financial data is a plus
• Strong at Python (or equivalent – Rust / Go), algorithms, performance optimization
• Understanding of libraries such as NumPy, Pandas, polars, scikit-learn, etc
• Comfortable building solutions on AWS and leveraging cloud service provider infrastructure to solve complex problems
• Good engineering practice: TDD, code reviews, refactoring, branch management, CI/CD
• Excellent troubleshooting and problem-solving skills.
• Critical thinking: you question assumptions, check data and outputs (including, and especially AI-generated ones), and say so when something doesn't add up.
• Systems thinking: you see how data, services, clients and people interact; you design for the whole flow, considering edge cases and downstream effects, not just the ticket at hand.
• Strong written and verbal communication. You can explain technical work to non-technical stakeholders and tell the story behind your work.

Our Tech & Tools

• Backend: Python (analytics runtime compute engine, data integrations) and TypeScript/Node.js; AWS Lambda for data processing pipelines
• Data: Aurora (MySQL), Postgres, DynamoDB, S3; data from multiple providers via SFTP, custom loaders and APIs
• AI: LLM-powered product features and agentic workflows; AI coding agents across the engineering team
• Frontend: React, TypeScript, Next.js
• Infrastructure: Serverless (AWS Lambda, SQS, Fargate); AWS and IAC throughout

Please note that this is a 6-months B2B contract, with high possibility of long-term extension.