Software Engineer — AI-Native Engineering at Chekin, UK, £Contractor Rate

About Us

At Chekin.com, we’re building the leading platform for hospitality check-in automation, covering the full guest journey from booking confirmation to check-out.

Today, we operate globally across thousands of properties and have grown into a profitable SaaS company, with ambitious plans to scale significantly over the coming years.

We are an AI-native company that believes technology, automation, and operational efficiency should be embedded into everything we do — from product development to internal workflows.

Our Product & Tech team is made up of ambitious, collaborative, and highly autonomous people who enjoy solving complex technical problems while moving fast.

The Role

We are looking for a Backend Engineer to join our Product & Tech team on a full-time B2B contractor basis.

The candidate is a backend-strong engineer who, with AI as a force multiplier, owns a slice of product end to end — from understanding the user problem through frontend, backend, tests, observability, rollout, and post-launch monitoring.

This role is ideal for someone highly autonomous, product-minded, and comfortable working in a fast-paced startup environment. You will contribute to the evolution of our backend architecture, scalability initiatives, integrations, automation systems, and AI-powered internal tooling.

We are looking for engineers who can take a product slice from a vague problem statement all the way to a stable, observed feature in production — not just the API behind it.

Backend depth remains the anchor. You are a backend engineer first. The rest of the stack is reachable through AI leverage and a willingness to own the full delivery lifecycle, not through pretending to be a senior frontend engineer.

One person, one feature, end to end.

Because of our operational and collaboration requirements, candidates must currently reside in the European Union and be available to work on a full-time B2B contractor basis.

What You’ll Be Doing

• Take a vague product problem, understand the user and business context, sharpen it into a clear scope, and ship it — without waiting to be told exactly what to build.
• Own a product slice end to end, from problem definition through production stability.
• Design and build the backend: APIs, data models, services, integrations, and business logic. This is your deep craft.
• Build the frontend for the features you own, using AI assistance to accelerate scaffolding, framework-specific patterns, and implementation.
• Write tests at every relevant layer — unit, integration, and end-to-end — and use AI to expand coverage rather than skip it.
• Define the observability plan before you ship: logs, metrics, traces, dashboards, alerts, and the product metric that proves the feature worked.
• Own the rollout: feature flags, gradual ramp-up, rollback plans, and communication with relevant stakeholders.
• Be accountable for the production behaviour of the features you ship and close the loop on incidents when something goes wrong.
• Read the metrics after launch, talk to users when needed, and decide what to change next.
• Document your work through design docs, README updates, changelogs, post-mortems, and other relevant documentation.
• Use AI to review and challenge your own work before it reaches a human reviewer.

AI-Native Engineering

AI fluency is not a bonus skill in this role. It is a core part of how we expect the candidate to work.

The expanded scope of this role is only realistic when AI is used as a force multiplier. We expect engineers to actively use AI tools to improve development speed, code quality, debugging, testing, documentation, automation, and their ability to work across the stack.

Experience with tools such as:

• ChatGPT
• Claude
• Claude Code
• Gemini
• AI coding agents and developer tooling

We are especially interested in people who naturally use AI to:

• Accelerate frontend development and navigate unfamiliar frameworks.
• Eliminate repetitive boilerplate such as DTOs, mappers, CRUD, and configuration.
• Generate edge cases and expand test coverage.
• Draft dashboards, alert rules, and runbooks.
• Create and maintain technical documentation.
• Review their own code and identify potential issues before submitting a PR.
• Accelerate migrations and large-scale refactors.
• Automate workflows and reduce operational overhead.

Our Ideal Candidate Has

• 4+ years of backend engineering experience with a strong track record of shipping production services in a mainstream language such as Go, Python, Java, Kotlin, TypeScript, Rust, or C#.
• Strong backend fundamentals and the ability to design reliable APIs, data models, services, and integrations.
• A solid grasp of distributed systems fundamentals, including concurrency, failure modes, idempotency, and backward compatibility.
• A willingness and ability to own frontend work when it is part of the product slice you are delivering. You do not need to be a senior frontend engineer, but you should be comfortable using AI assistance to build and ship UI work.
• Demonstrated AI-assisted development fluency. You use AI tools regularly, understand where they help and where they mislead, and can show concrete examples of how they have accelerated your work.
• A production ownership mindset. You have built and operated services, written observability that you actually relied on during incidents, and treated post-launch monitoring as part of the work.
• Strong product instinct. You can understand a user problem, challenge a specification when necessary, and shape scope based on user and business goals — not just implement what is handed to you.
• A strong sense of ownership and autonomy. You are comfortable taking responsibility for a feature without needing every step defined in advance.
• Strong written and verbal communication. You write clear design documents, leave thoughtful PRs, document decisions, and explain trade-offs without hand-waving.

Technical Stack

Must Have

• Strong backend engineering experience in at least one mainstream programming language.
• Experience designing and building production APIs and backend services.
• Experience with relational databases and data modelling.
• Experience with automated testing and production observability.
• Experience deploying and operating production software.
• Strong experience using AI-assisted development tools as part of your daily engineering workflow.

Nice to Have

• Experience with Python and Django.
• Experience with PostgreSQL.
• Experience with Docker and AWS.
• Experience with Kubernetes / AWS EKS.
• Experience with React and TypeScript.
• Experience with Selenium or browser automation.
• Experience working in SaaS or high-growth startups.

What We Offer

• Full-time B2B contractor agreement.
• Fully remote setup within the European Union.
• Flexible working hours.
• High ownership and autonomy.
• The opportunity to own product features end to end, from problem definition to production stability.
• The opportunity to work directly on impactful technical challenges in a fast-growing international SaaS company.
• A fast execution environment with minimal bureaucracy.
• A highly AI-oriented engineering culture focused on efficiency, automation, and leverage.
• A role where backend engineering depth remains your anchor while AI enables you to work across the full product lifecycle.

This role is not for you if…

• You strongly prefer to stay inside a single layer of the stack and expect other people to own everything outside it.
• You see AI tooling as a fad or refuse to integrate it meaningfully into your daily workflow.
• You expect to hand off the frontend, tests, observability, rollout, or post-launch monitoring to someone else.
• You want to ship and walk away — production stability and post-launch ownership are part of the job.
• You want a pure individual-contributor coding role with no product thinking attached.
• You need every task to be fully specified before you can start making progress.
• You are looking for a role where being a strong backend engineer means you never need to understand the user problem or the broader product context.