Accountabilities:

Design, develop, and deliver core software infrastructure supporting privacy-preserving AI evaluations, primarily using Python.
Build, maintain, and strengthen secure enclave solutions and Trusted Execution Environment (TEE) technologies to enable confidential computing.
Contribute to the development and evolution of PySyft, an open-source library, including its workers, verified receipts, and related infrastructure.
Develop scalable, secure, and reliable software components that enable external evaluators to assess advanced AI models while protecting sensitive data and intellectual property.
Deploy, configure, and support software within partner environments, including frontier AI laboratories, independent evaluation organizations, and government institutions.
Help scale the platform from its initial production deployment to multiple implementations, improving reliability, performance, scalability, and overall user experience.
Take ownership of significant engineering components, making sound architectural decisions and ensuring long-term maintainability.
Write clean, readable, efficient, and well-tested code while maintaining high software engineering standards.
Participate in code reviews, provide constructive feedback, and contribute to shared engineering practices.
Translate ambiguous technical and business requirements into clear system designs, implementation plans, and practical solutions.
Communicate architectural decisions, technical trade-offs, project timelines, and potential risks effectively to both technical and non-technical stakeholders.
Leverage AI-powered coding tools to accelerate development while maintaining code quality, security, and reliability.
Collaborate with technical leadership and distributed engineering teams to continuously improve products and infrastructure.

Requirements

At least 5 years of professional software engineering experience, with strong hands-on proficiency in Python.
Excellent coding abilities, with a demonstrated commitment to writing clean, maintainable, readable, reliable, and thoroughly tested software.
Strong understanding of software architecture, systems design, and engineering trade-offs, with the ability to develop robust solutions that minimize future technical rework.
Proven full-stack development experience on at least one project, covering multiple areas such as backend engineering, data, frontend development, and deployment.
Experience with CI/CD pipelines, complex system debugging, and cloud infrastructure.
Good understanding of software security, scalability, performance, and reliability principles.
Strong analytical and problem-solving abilities, with the capacity to quickly understand unfamiliar technical concepts and translate them into practical solutions.
Excellent written and verbal communication skills, including the ability to explain technical concepts, timelines, risks, and architectural decisions clearly and concisely.
Ability to work collaboratively within a small, fully remote team, demonstrating adaptability and openness to constructive feedback.

Preferred Qualifications

Experience with Trusted Execution Environments (TEEs), secure enclaves, confidential computing, or other security-focused technologies.
Knowledge of distributed systems and experience building scalable, distributed software architectures.
Previous experience deploying and maintaining software within external organizations' infrastructure and technical environments.
Familiarity with Terraform, Kubernetes, and cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS).
Experience or knowledge in AI safety, privacy-enhancing technologies, or large language models (LLMs).
Contributions to open-source software projects, particularly maintaining personal repositories or making significant contributions to established projects.
Experience developing software products and tools for technical users and developer communities.
Previous experience working in a startup or fast-paced technology environment.
Proficiency in a lower-level programming language such as Rust, Go, or C++ for performance-critical applications.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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