Product Engineer

We are building a next-generation product engineering organization where engineers take ideas from concept to market-ready products. The Product Engineer combines strong software engineering fundamentals with AI tools to design, build, test, and operate product components.

• Drive end-to-end product development, taking features from concept to production with minimal supervision.
• Build, ship, and iterate rapidly to meet business deadlines and user requirements.
• Collaborate closely with product managers and designers to translate user needs into technical specifications and acceptance criteria.
• Write high-quality, scalable code and ensure the performance and maintainability of the codebase.
• Analyse complex systems and resolve technical issues from development to production.
• Use AI coding assistants and agents to accelerate development of product features. Generate, review, and refine code produced by AI tools.
• Take full responsibility of unit testing and ensure bug-free code is delivered. Also, validate correctness, security, and performance of AI-generated code.
• Design and implement: Microservices, APIs and integration services, Data pipelines, Event-driven architectures, Domain services
• Ensure all components are: Scalable, Observable, Secure, cloud-ready, and maintainable for the long term.
• Use modern AI frameworks to automate engineering workflows such as: Code generation, Test creation, Documentation, Refactoring, Debugging
• Ensure high product quality by reviewing AI-generated code, writing automated tests, and performing performance and security reviews
• Work with modern DevOps practices which include adhering to defined CI/CD pipelines and building all components for cloud-native deployment.

• Strong experience in at least one major programming language such as: Java, Python, Go, TypeScript
• Experience with Microservices architecture, REST / GraphQL APIs, Distributed systems, Databases (SQL and NoSQL)
• Experience using AI engineering tools such as GitHub Copilot, Cursor, Claude, etc.
• Ability to evaluate AI-generated code, integrate AI tools into development workflows
• Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform with focus on containers and orchestration, infrastructure automation and observability tools
• Domain-driven design
• Platform engineering
• AI/ML system integration
• Event-driven architectures
• Product thinking
• Experience level: 5 to 8 years