Software Engineer Backend

London, ENG, GB, United Kingdom

Job Description

The Role



We're hiring a Software Engineer (Backend) to help us build the AI-native infrastructure to solve critical failures in residential real estate. As an early engineer, you will have significant ownership over technical decisions that determine whether we fundamentally reshape the industry forever.

You will be a part of building a hyper-efficient, AI/ML-native consumer-facing, capital efficient, service company for a large market. You will write the software that pushes hard on the capabilities of AI/ML models as they function in the real world, with real people's money, jobs, and property.

Key Responsibilities



Design, develop, and maintain scalable, event-driven microservices architecture Build and optimise RESTful APIs following best practices and design patterns Own the deployment and operation of services on Kubernetes Ensure reliability, security, and performance through testing, monitoring, and optimisation Collaborate closely with AI engineers to integrate LLM/ML solutions into backend services Contribute to system architecture decisions and long-term technical roadmap planning Participate in DevOps, infrastructure, and database management, including CI/CD pipelines and GitOps workflows

Technical Requirements



Strong proficiency in one backend language (TypeScript/Node.js, C#, Java, etc.) Experience with backend frameworks such as NestJS, Spring, or .NET Core (NestJS + TypeScript in our stack) Experience with microservices architecture, including event-driven systems Deep knowledge of RESTful API design and implementation Proficiency with containerisation and orchestration using Kubernetes (we use GKE) Database experience across paradigms (MongoDB in our stack) Strong understanding of authentication/authorization and secure coding practices (Auth0 in our stack) Solid experience with automated testing (unit, integration, e2e) Experience designing scalable, resilient, and high-performance systems Hands-on experience with CI/CD pipelines and infrastructure as code (Kustomize in our stack) Familiarity with cloud-native services (e.g. Pub/Sub, IAM, secret management, monitoring) Familiarity with Git workflows and collaborative development Familiarity with ArgoCD and GitOps practices (used in our stack) Familiarity with LLM integrations and AI/ML concepts Bonus: Experience with modern frontend frameworks (Angular in our stack)

Essential Characteristics



Hyper-focus on detail: you need to write clean, maintainable, well-documented code First principles reasoning: you approach complex technical challenges thoughtfully Communication clarity: you can articulate complex technical concepts to all Ownership mentality: you are a self-guided missile who drives initiatives forward Collaborative: you know that teams change the world, not individuals Adaptability: you thrive in a fast-paced environment with evolving requirements Learning velocity: you are able to quickly master new paradigms and changes Quality-obsessed: everything you do needs to be of a high quality

About Letly



Letly exists to re-build the infrastructure for residential real estate on an AI/ML-native foundation. Real Estate is broken everywhere. The whole market operates against consumer interests; governments have failed to intervene to fix it; incumbents have taken advantage with extractive fees for human labour-intensive workflows. In all this ~$825bn is paid in rent annually across the UK and US. Incumbent agencies charge 10-20% for property management and compete against each other - all with inefficient businesses.

We're building AI-native infrastructure to delete this pain entirely. We quietly raised a $1m Pre-Seed three months ago, and our founding team combines frontier domain-specific AI expertise with scale infrastructure experience.

Job Type: Full-time

Projected Total Compensation: From 70,000.00 per year

Work Location: In person

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Job Detail

  • Job Id
    JD3820743
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    London, ENG, GB, United Kingdom
  • Education
    Not mentioned