Senior Software Engineer

Steradium · Philippines · posted today ago

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About this role

Steradium is a technology company focused on turning advanced artificial intelligence into practical solutions for businesses. Our team members collaborate in a modern, fast-paced environment that values curiosity, problem-solving, and continuous learning. We're currently building an AI-native engineering team from the ground up.

What you'll do

The Senior Software Engineer will design, build, and maintain scalable software systems that power Steradium’s AI-driven products and services.
Day-to-day responsibilities include implementing robust back-end services, writing clean and testable code, reviewing code from peers, and contributing to architectural decisions for new and existing platforms.
The role also involves collaborating with data scientists and product teams to integrate AI models, optimize performance, and improve reliability.
This is a full-time remote role, requiring strong communication skills, ownership of deliverables, and the ability to work effectively in a distributed team environment.

What we're looking for

Strong foundation in Computer Science, including algorithms, data structures, and software design principles.
Hands-on experience with software development using modern languages and frameworks to build production systems.
Expertise in Back-End Web Development, including APIs, microservices, and database integration.
Solid fundamentals in data modeling, async behavior, caching, HTTP semantics, and authentication.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization/orchestration tools (e.g., Docker, Kubernetes).
Comfort with version control (Git), CI/CD pipelines, and automated testing practices.
Ability to lead technical initiatives, mentor other engineers, and contribute to architectural decisions.
Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.
Experience working on AI/ML-powered products or data-intensive systems is a plus.

How we work with AI

Every engineer here has Claude Code in their daily loop. We measure output in shipped, reviewed, production-grade work, not in hand-typed lines.
Everyone can use AI assistants for scaffolding, refactors, test generation, and exploring unfamiliar codebases, but you own every line that ships with your name on it.
We expect everyone to know and understand where AI is unreliable: subtle concurrency, security boundaries, domain logic, anything where being confidently wrong is expensive.