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About Canbury Insights
Canbury is a technology-enabled sustainability consultancy applying AI tools to deliver research, data, and analysis thoroughly, effectively, and cost-efficiently. We work with leading institutional investors, companies, and NGOs on specialized sustainability topics, including climate change, nature, social inequality, systems change, and policy change.
Alongside the advisory business, we build and run our own data platform. It combines structured ESG data with AI-assisted analysis of company disclosures. This opportunity offers the chance to work on and shape the strategy of a product used by institutional clients.
You can find more on our service lines and examples of our work at canbury.io.
The role
This is a first engineering role for someone who has just finished a computer science degree, or is within a year of it. You will be given well-scoped pieces of work on our data and AI pipelines, with a senior engineer close by.
The role is deliberately not client facing. You will not be asked to sit in front of an asset manager or present findings. Your job is to write good code, understand what it does, and care about whether the output is correct.
You will:
- Build and extend components of our data ingestion and assessment pipelines in Python
- Write and maintain the checks, tests, and validation logic that tell us when a pipeline has produced something wrong
- Work with structured company and portfolio data in PostgreSQL, including writing and tuning queries
- Help run assessments across large sets of companies, and investigate outputs that look wrong
- Build internal tooling and scripts that make the rest of the team faster
- Keep documentation current so that the next person can pick up your work
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On the use of AI tools
We expect you to use AI coding tools such as Claude Code, and we will pay for them. We are not interested in candidates who avoid them on principle.
What we do care about is that you can explain and defend what the tool produced. In interview we will ask you to walk through code you have written with AI assistance: why it is structured that way, where it would break, what you checked before trusting it.
What we are looking for
Essential
- A degree in computer science, software engineering, or a closely related quantitative subject
- Sound programming fundamentals and real fluency in Python, whether from coursework, internships, or personal projects
- Working knowledge of SQL and relational databases
- Comfort with version control and normal collaborative development practice
- Demonstrable, thoughtful use of AI coding assistants, and the ability to explain code produced with them
- Care about correctness, and the instinct to check output rather than assume it is right
- Clear written communication with colleagues, and a willingness to ask when something is unclear
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Desirable
- Internship or placement experience, or substantial personal or open-source projects
- Any hands-on exposure to large language model APIs beyond using a chat interface
- Cloud exposure, ideally Microsoft Azure
- Interest in sustainability, climate, or financial markets. No prior knowledge is expected
What success looks like
Within three months: picking up well-defined tasks and shipping them without needing the approach explained twice.
Within twelve months: owning a small component of the platform, trusted to spot when something looks wrong before anyone else does, and able to explain the domain well enough to be useful in internal discussions about methodology.
Why the role is interesting
A small team, real product work from the start, and applied AI engineering rather than a graduate scheme rotation. You will see how the work reaches the client, and you will be given more responsibility as soon as you can carry it.
Interview process
Three stages after the initial recruiter screen:
- Introductory call with the Chief Technology Officer
- Technical exercise and discussion with the engineering team
- Final conversation with one of the founders
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