Talan is hiring a Senior Fullstack Java/Angular

As a Senior Full Stack Developer, your goal will be to participate in the development of a new issuance monitoring and management application, as well as Distribution, Pricing and Processing platform. We are looking for an AI-native engineer with a strong software engineering mindset, capable of leveraging modern AI tools and practices across the entire Software Development Life Cycle (SDLC), from requirements analysis and solution design to development, testing, deployment, monitoring, and continuous improvement. You will work in a collaborative Agile environment, contributing to the design and implementation of scalable, secure, and high-quality enterprise applications. Resposibilities - Participate in the design, development, and maintenance of innovative enterprise applications. - Collaborate with business stakeholders and technical teams to analyze requirements and define technical solutions. - Mentor junior developers and contribute to a strong engineering culture. - Design and develop new application modules and microservices-based solutions. - Develop and maintain backend and frontend components using modern technologies and frameworks. - Create and execute test cases, ensuring software quality and reliability. - Participate in CI/CD processes, deployments, and production support activities. - Diagnose and resolve incidents, performance bottlenecks, and application issues. - Contribute to architecture discussions, technical decisions, and best engineering practices. - Use repositories, DevOps pipelines, and software development tools efficiently. - Promote clean code, maintainability, observability, and security best practices. AI-Native Engineering Responsibilities - Leverage AI-assisted development tools throughout the SDLC to improve productivity, quality, and delivery speed. - Use AI coding assistants and autonomous engineering tools such as: - Devin, GitHub Copilot, Cursor. ChatGPT, Claude, Gemini, Sourcegraph Cody, Continue.dev Apply AI-driven approaches for: - Code generation and refactoring - Automated documentation - Test generation and validation - Debugging and root cause analysis - Code reviews and quality improvements - SDLC automation and developer productivity optimization - Understand the capabilities, limitations, and appropriate usage of Large Language Models (LLMs) in software engineering workflows. - Collaborate in the adoption of AI engineering best practices, governance, and secure usage of AI tools in enterprise environments. - Stay up to date with emerging AI engineering trends, frameworks, and development accelerators.