Full Stack Engineer

Full Stack Engineer

Full-Time 40000 - 60000 £ / year (est.) Home office (partial)
Canbury

At a Glance

  • Tasks: Build and own infrastructure, develop full-stack features, and create AI/data pipelines.
  • Company: Canbury, a tech-driven sustainability firm using AI for impactful research.
  • Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
  • Other info: Join a small, dynamic team with excellent career development opportunities.
  • Why this job: Make a real difference in sustainability while working with cutting-edge technology.
  • Qualifications: 2+ years of software engineering experience and strong DevOps skills.

The predicted salary is between 40000 - 60000 £ per year.

About Canbury

Canbury is a technology-enabled sustainability firm applying AI tools to deliver research, data, and analysis thoroughly, effectively and cost-efficiently. We work with leading institutional investors, companies and NGOs on specialised sustainability topics, including climate change, nature, social inequality, systems change, and policy change. We combine deep sustainability and financial expertise with our in-house technology team to develop bespoke software solutions for clients across the sustainability space. We are at the forefront of deploying AI into sustainability data, using technology where it is best applied to reduce manual time and cost on large-scale text and data analysis.

About the role

We are expanding our technology team to meet growing client demand. As a Full-Stack Engineer, you will work across our internal platform, which powers Canbury’s research and analytics, and bespoke software for clients across the sustainability space. Our stack is Python (FastAPI), React/TypeScript, PostgreSQL, and Azure (Container Apps, Blob Storage, Postgres Flexible Server, and related services). You will work across all of it. We are particularly keen to hear from engineers with strong infrastructure and DevOps instincts who want to push us to run things properly in production.

Why this role is interesting

  • Real autonomy. We are a small team. You will scope, build, deploy, and own systems end-to-end.
  • AI in production. We run LLM pipelines processing thousands of company disclosures for institutional investors. Cost, latency, and reliability are real constraints.
  • Technical breadth. Infrastructure, full-stack product work, and AI/data engineering all sit within the role.
  • Work that matters. Our clients steward trillions in assets. The tools you build shape how they assess companies on sustainability.

What you'll do

  • Build and own infrastructure on Azure.
  • Design and maintain CI/CD pipelines, container deployments, networking, secrets management, monitoring, and cost controls.
  • Develop full-stack features end-to-end. From Postgres schema design through FastAPI endpoints to React interfaces, for client deliverables.
  • Build Python-based data and AI pipelines. Develop analytics and ETL pipelines, automate data collection and cleansing, and extract insights via LLM APIs (Anthropic, OpenAI, Gemini).
  • Optimise for cost and quality through caching, batching, token management, and prompt and post-processing design.
  • Contribute to technical decision-making as the team grows: architecture, tooling, code quality, and engineering practices.
  • As a small team, everyone wears multiple hats and the role will evolve with the business and with technological developments.

What we're looking for

  • At least 2 years of professional software engineering experience, preferably in roles where you have shipped and operated production systems, not just built prototypes.
  • Strong infrastructure and DevOps skills: hands-on experience with Azure (or comparable cloud, AWS or GCP), containerisation (Docker), CI/CD, and infrastructure-as-code.
  • Solid full-stack experience with Python backends (FastAPI or similar), React/TypeScript frontends, and relational databases (PostgreSQL preferred).
  • A track record of building and shipping. Personal projects, open-source contributions, or production systems you can talk about in detail.
  • Comfort working with LLM APIs and an understanding of the practical considerations around cost, latency, and reliability when AI is in the loop.
  • Pragmatism and ownership. We need people who can scope, build, deploy, and maintain, not just write code and hand it off.

Practicalities

  • Location: London. Hybrid. We have an office in Farringdon.
  • Type: Full-time, permanent.
  • Salary: £40k-60k+ depending on experience.
  • Right to work: You must have the right to work in the UK. We are unable to sponsor visas at this stage.

Full Stack Engineer employer: Canbury

At Canbury, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our team members to take ownership of their projects. Located in the vibrant area of Farringdon, London, we offer a hybrid working model that promotes work-life balance while providing opportunities for professional growth in the rapidly evolving field of sustainability technology. Join us to make a meaningful impact as you develop cutting-edge AI solutions that drive positive change in the world.
Canbury

Contact Detail:

Canbury Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Full Stack Engineer

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with Canbury employees on LinkedIn. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, React, or Azure. This gives us a glimpse of what you can do and makes you stand out from the crowd.

✨Tip Number 3

Prepare for the tech interview! Brush up on your full-stack knowledge and be ready to discuss your experience with CI/CD, containerisation, and AI pipelines. We love seeing candidates who can talk about their hands-on experience.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in joining our team at Canbury.

We think you need these skills to ace Full Stack Engineer

Python
FastAPI
React
TypeScript
PostgreSQL
Azure
Containerisation (Docker)
CI/CD
Infrastructure-as-Code
DevOps
Data Engineering
LLM APIs
ETL Pipelines
Analytical Skills
Problem-Solving Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Full Stack Engineer role. Highlight your experience with Python, React, and Azure, and don’t forget to mention any relevant projects or contributions you've made!

Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for sustainability tech. Explain why you’re excited about the role and how your background makes you a great fit for our team at Canbury.

Showcase Your Projects: We love seeing what you’ve built! Include links to your GitHub or any personal projects that demonstrate your full-stack capabilities and DevOps skills. This gives us a real sense of your hands-on experience.

Apply Through Our Website: To make sure your application gets to us directly, apply through our website. It’s the best way to ensure we see your application and can get back to you quickly!

How to prepare for a job interview at Canbury

✨Know Your Tech Stack

Make sure you’re well-versed in the technologies mentioned in the job description, especially Python (FastAPI), React/TypeScript, and PostgreSQL. Brush up on your Azure skills too, as they’ll be crucial for the role. Being able to discuss your experience with these tools will show that you’re ready to hit the ground running.

✨Showcase Your Projects

Prepare to talk about your past projects, especially those where you’ve built and operated production systems. Highlight any personal projects or open-source contributions that demonstrate your full-stack capabilities and DevOps instincts. This is your chance to show how you’ve scoped, built, and maintained systems end-to-end.

✨Understand AI Integration

Since the role involves working with AI and LLM APIs, make sure you understand the practical considerations around cost, latency, and reliability. Be ready to discuss how you’ve optimised data pipelines or any relevant experiences you have with AI in production. This will show that you can think critically about the challenges involved.

✨Emphasise Ownership and Pragmatism

Canbury values autonomy and ownership, so be prepared to discuss how you take responsibility for your work. Share examples of how you’ve contributed to technical decision-making and improved engineering practices in your previous roles. This will demonstrate that you’re not just a coder but a proactive team player who can drive projects forward.

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