As an AI Enablement Engineer at FairMoney, you will help drive the adoption of AI-assisted engineering practices across our technology teams. You will work closely with engineering squads to identify opportunities where AI can improve development workflows, developer productivity, automation, and the overall software delivery process.
This is a hands-on role for someone who enjoys building, experimenting, automating, and working directly with engineers to turn new AI capabilities into practical engineering solutions.
If you are passionate about AI, developer tooling, automation, and improving the way software teams build and deliver products, we want you to join our team!
We are looking forward to having you work on:
- Supporting the adoption of AI-assisted engineering practices across engineering squads;
- Building scripts, automations, and developer tools that improve engineering productivity;
- Working directly with engineers to identify and implement practical AI use cases across development workflows;
- Experimenting with AI coding tools and agents and developing reusable workflows and best practices;
- Providing hands-on support to squads and continuously improving AI adoption across the engineering organisation.
Our customer-facing product is an Android application;
- It communicates with Ruby on Rails or Go-lang backends (Sidekiq, RSpec);
- Our ML pipeline is API-Flask (Python);
- We are hosted on AWS: Kubernetes, SNS, SQS, Lambdas, RDS Aurora MySQL and PostgreSQL, DynamoDB, S3, and Kinesis;
- Prototype of a data warehouse on GCP (GCS, BigQuery, Cloud Composer);
- We run our CI/CD pipeline with GitHub Actions;
- AI-assisted development and developer productivity tooling.
- 3+ years of experience in software engineering, developer tooling, automation, or a related technical role;
- Hands-on experience with AI-assisted software development and modern AI coding tools;
- Strong scripting and automation skills, with proficiency in at least one programming language such as Python, Go, JavaScript, or Ruby;
- Experience building internal tools, automation, or developer workflows;
- Strong problem-solving skills and the ability to translate engineering challenges into practical technical solutions;
- Willingness to work directly with engineering squads and support them hands-on.
- Experience working with AI coding assistants, AI agents, LLM-based developer tools, or similar technologies;
- Experience building developer tooling or platforms that improve engineering productivity;
- Experience integrating APIs and third-party tools into engineering workflows;
- Knowledge of software engineering practices across the full development lifecycle, including coding standards, code reviews, source control, testing, CI/CD, and operations;
- Experience working with cloud providers, preferably AWS, alternatively GCP/Azure;
- Familiarity with microservices and modern software development architectures;