Posted 1 month ago
Full stack Engineer
AI Summary
A full stack software engineer designs and builds internal engineering tools, reusable CI/CD templates, and proofs of concept; evaluates and scales AI-assisted development tools; and collaborates with multiple stakeholders to deliver production-ready solutions that improve developer productivity and software delivery.
About this role
We are looking for a Full stack Software Engineer to improve engineering productivity through automation, reusable development capabilities, AI-assisted engineering practices, and rapid experimentation with new technologies.
In this role, you will design and build internal engineering tools, reusable CI/CD templates, reference implementations, and proofs of concept. You will also help evaluate and scale AI-based development tools and establish practical, secure, and effective ways for engineering teams to use them.
You will work closely with Engineering, Product, QA, DevOps, Security, and other stakeholders to deliver scalable, maintainable, and production-ready solutions that improve how software is developed, tested, deployed, and operated.
Key Responsibilities
- Design, build, and maintain reusable CI/CD templates, pipelines, and automation capabilities that can be adopted across engineering teams.
- Identify manual or inefficient engineering processes and implement automation that improves development speed, consistency, quality, and reliability.
- Evaluate, implement, and scale AI-assisted engineering tools and practices across the software development lifecycle.
- Define practical best practices and guidelines for the secure and effective use of AI tools in coding, testing, documentation, code review, and engineering workflows.
- Build internal tools, reference applications, and integrations that improve developer productivity and the overall developer experience.
- Research emerging technologies, engineering patterns, and development tools, and create proofs of concept to assess their technical and business value.
- Translate successful proofs of concept into maintainable, production-ready solutions where appropriate.
- Build and deploy applications and services in modern cloud-based and containerised environments.
- Contribute to architectural and technical decisions related to developer tooling, automation, CI/CD, cloud platforms, AI enablement, observability, and software delivery.
- Establish appropriate monitoring, testing, documentation, and operational practices for the solutions you build.
Share knowledge through documentation, demonstrations, workshops, and collaboration with engineering teams.
- Work closely with Engineering, Product, QA, DevOps, Security, and governance stakeholders to ensure that solutions meet technical, business, security, and compliance requirements.
Must-Have Qualifications
- Extensive engineering experience.
- Hands-on experience building and maintaining production-grade software applications.
- Experience building backend services and APIs using Java.
- Experience with containerised development and deployment using Docker or equivalent technologies.
- Strong understanding of software engineering practices, including clean code, design patterns, automated testing, maintainability, monitoring, and observability.
- Experience working with relational databases.
- Experience integrating applications or services with internal and external systems.
- Strong analytical, problem-solving, collaboration, and communication skills.
- Professional fluency in English.
- Bachelor's degree in computer science, Software Engineering, or a related field, or equivalent practical experience.
Nice-to-Have Qualifications
- Experience with GitHub, GitHub Actions, GitHub Copilot, or similar platforms and tools.
- Experience developing reusable CI/CD templates or shared engineering workflows used across multiple teams.
- Scripting experience using Python, Bash, PowerShell, or similar languages.
- Experience with one or more major cloud platforms, such as AWS, Microsoft Azure, or Oracle Cloud Infrastructure.
- Experience evaluating new technologies and turning proofs of concept into production-ready solutions.
- Knowledge of AI governance, secure AI usage, data protection, or intellectual-property considerations related to AI-assisted software development.
- Experience defining or measuring developer productivity, platform adoption, or engineering effectiveness.
- Background in financial services or another regulated industry.
Skills
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