AI Software Engineer

About the Role

Join our team as an AI Software Engineer where you'll be fully engaged in an Agile, multifaceted product team. Your role will encompass designing, developing, testing, and maintaining critical digital software solutions. You'll take ownership of delivering practical, scalable features from the product roadmap and contribute across the entire software lifecycle to create secure, maintainable solutions closely aligned with user requirements. Candidates with 1 to 3 years of relevant experience are welcomed, as are new graduates possessing solid fundamentals along with internship or project experience.

Unique Role Highlights

In contrast to companies that segment roles for frontend, backend, QA, DevOps, and platform tasks, here you will own the full spectrum of your product's lifecycle—from grasping user needs to delivering and operating solutions. Embracing AI-assisted development is integral; engineers utilize modern AI tools and autonomous workflows to boost productivity, speed delivery times, and elevate quality.

Key Responsibilities

• Develop, maintain, and deploy production-level software applications.
• Create both frontend user experiences and backend services solving operational challenges.
• Translate business needs into efficient and functional software.
• Engage in architectural and technical design sessions.
• Integrate AI-driven functionalities utilizing modern language models and autonomous workflows.
• Assess emerging AI technologies for practical operational benefits.
• Design hybrid software solutions incorporating both traditional engineering and AI features with a focus on security and maintainability.
• Develop cloud native applications hosted on Kubernetes platforms.
• Implement continuous integration and delivery systems aligned with GitOps principles to automate builds, deployments, and operations.
• Enhance reliability, scalability, observability, and maintainability of systems.
• Write clear, testable, and maintainable code adhering to quality standards.
• Consider security, governance, and operational readiness during solution design.
• Support live systems by troubleshooting issues as they arise.
• Collaborate closely with cross-functional teams including product managers, UI/UX designers, and business stakeholders.
• Participate actively in user and operational discovery to inform better product development.
• Contribute to fostering a culture of ownership, continuous learning, and engineering excellence.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field.
• Practical experience in application development using contemporary programming languages.
• Good grasp of software engineering principles such as version control, testing methodologies, and system architecture.
• Experience or familiarity with cloud native development practices.
• Strong analytical thinking and problem-solving abilities.
• Eagerness to continuously learn and adapt as AI technologies evolve rapidly.
• Exposure to AI concepts including large language models (LLMs), agent orchestration, or retrieval systems.
• Proficient in Python and modern web frameworks.
• Experience with FastAPI and React or related technologies.
• Knowledge of Kubernetes and containerized application deployment.
• Experience working with CI/CD pipelines and Git workflow automation.
• Background in building and maintaining production-grade software systems.

Ideal Candidate Profile

You thrive when tackling complex technical challenges and are motivated to build impactful products that users rely on. You are versatile and comfortable engaging with different layers of the technology stack, ready to assume broad ownership. You have an interest in AI technologies but recognize that successful software products require a balance of code quality, security, operations readiness, and great user experience. Your primary focus is on meaningful outcomes, not just coding.

Success Metrics

• Delivered features that are production-ready and actively used within the first year.
• Contributed to the expansion and quality of an operational product.
• Enhanced engineering workflows through automation and AI-powered development tools.
• Helped define and uphold engineering best practices and standards.
• Demonstrated end-to-end ownership from conceptualization through to production operations.