Software Engineer – Full-Stack Development

Job description

Software Engineer – AI-Assisted Full-Stack Development Location: Remote within the EU or an EU-compatible time zone (1/2 hours) Work model: Remote No. of position: 1 1 junior/entry level, computer science graduate, with top grades and great knowledge of AI coding agents - especially Claude Experience: Maximum 1-2yrs About DATAmundi DATAmundi builds advanced software solutions that power our data service We are seeking a Software Engineer who can design, build, test, deploy, and maintain reliable software using Claude Code or similar AI coding agents as part of their daily engineering workflow. The role is open to both experienced engineers and promising junior candidates who demonstrate strong technical foundations, initiative, and the ability to learn quickly. Key Responsibilities Software Development Design, develop, and maintain scalable web applications using Python, FastAPI, React, JavaScript or TypeScript, and Node.js. Design and implement REST or GraphQL APIs, including schemas, resolvers, authentication, authorization, validation, and error handling. Proficiency in both API styles is not required. Use Claude Code or similar AI coding agents to accelerate development while maintaining code quality, security, test coverage, and maintainability. Work with SQL and NoSQL databases, including data modelling, migrations, query optimization, and performance troubleshooting. Use message queues such as RabbitMQ for asynchronous processing, background jobs, and parallel workloads. Investigate and resolve complex bugs, production issues, and performance bottlenecks. Write clear technical documentation for APIs, system behaviour, and implementation decisions. Testing and Quality Write and maintain unit, integration, API, and end-to-end tests. Apply automated testing practices throughout the development lifecycle rather than treating testing as a final-stage activity. Familiar with tools such as Playwright for browser-based and end-to-end testing. Participate in code reviews and help maintain consistent engineering and quality standards. Validate AI-generated code through testing, review, security checks, and performance analysis. Contribute to continuous quality improvement by identifying recurring defects and improving test coverage and development processes. Delivery and Operations Work with Git and GitHub using feature branches, pull requests, code reviews, and documented release processes. Contribute to CI/CD pipelines, preferably using GitHub Actions or similar tools. Support application deployment and maintenance in cloud environments such as DigitalOcean, AWS, Azure, or GCP. Work with basic infrastructure concepts including containers, environment configuration, secrets, networking, databases, application services, and deployment pipelines. Use monitoring, logging, error-tracking, and session-replay tools such as Grafana, Sentry, and equivalent platforms. Help diagnose production issues using logs, metrics, traces, error reports, and session recordings. Collaboration and Ways of Working Work as part of an Agile Scrum team. Participate actively in sprint planning, backlog refinement, daily stand-ups, sprint reviews, and retrospectives. Break requirements into clear, estimable technical tasks. Communicate progress, risks, dependencies, and blockers clearly. Collaborate with product managers, software engineers, QA specialists, data scientists, and external development partners. Work effectively with minimal supervision while seeking clarification when requirements or technical constraints are unclear. Remain open to learning and working across multiple technologies. Required Qualifications Practical software design and development experience, gained through professional work, internships, academic projects, open-source contributions, or a strong technical portfolio. Experience using Claude Code or a similar AI coding agent to build, debug, test, or maintain software. Proficiency in Python and experience with FastAPI or a comparable Python web framework. Experience with React and JavaScript or TypeScript. Experience building back-end services using Node.js, Python, or both. Understanding of REST or GraphQL API design; proficiency in both is not required. Experience writing unit and integration tests. Understanding of relational databases and SQL. Familiarity with Git, GitHub, pull requests, and code-review workflows. Understanding of software engineering principles, including maintainability, modularity, security, and separation of concerns. Strong analytical, problem-solving, and communication skills. Ability to work independently in a remote environment. Professional working proficiency in English. Desired Skills and Experience Experience building GraphQL schemas, queries, mutations, subscriptions, and resolvers. Experience with GraphQL libraries such as Strawberry, Graphene, Ariadne, Apollo, or similar technologies. Experience with Playwright or another end-to-end testing framework. Familiarity with CI/CD platforms such as GitHub Actions, GitLab CI, Jenkins, or similar tools. Basic experience deploying or maintaining applications on DigitalOcean, AWS, Azure, or GCP. Familiarity with Docker and container-based application deployment. Experience with observability and production-support tools such as Grafana, Sentry, application logging platforms, or session-replay tools. Experience with message queues such as RabbitMQ, Kafka, Redis, or similar systems. Experience integrating AI or machine-learning models into production applications. Familiarity with authentication, role-based access control, API security, secrets management, and data-protection practices. Experience working in an Agile Scrum product-development environment. Education A Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline is preferred. Equivalent practical experience, demonstrable projects, or a strong technical portfolio will also be considered. What We Value Engineers who use AI tools to move quickly without compromising correctness or maintainability. A testing mindset and a strong sense of ownership. Curiosity and willingness to work across the full application lifecycle. Clear communication and constructive collaboration. The ability to turn product requirements into reliable, production-ready software.