À propos de ce poste Software Development Engineer II chez Safe
Most boards and executives are currently flying blind when it comes to cyber risk. They are guessing. At Safe, we’ve built an AI-driven engine that finally gives the C-Suite a clear, quantified, and real-time view of their security posture. We don’t just provide data; we provide certainty.
We are a $170M Series C-funded category leader. We don’t play in the mid-market; we operate at the highest levels of global enterprise. Today, we are proud to serve 10% of the Fortune 500, protecting global icons such as Apple, Netflix, AT&T, Verizon, and Victoria’s Secret.
As we scale toward our next chapter, we are looking for high-performers who want to do the best work of their careers at the intersection of AI and Cybersecurity.
The Culture Memo: Our Operating System
Safe is not a typical corporate environment. We are a high-intensity, mission-driven team. We value builders who want to define a category and work alongside people who are equally committed to excellence.
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Extreme Ownership: We don’t do "not my job." We hire people who see a gap and own the solution from start to finish.
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The Elite Standard: We serve the most sophisticated companies on the planet. Our work must be bulletproof. Whether it’s a line of code or a sales deck, we aim for Tier-1 quality every time.
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Methodology & Rigor: We don’t wing it. From Force Management and MEDDICC in sales to data-driven sprints in engineering, we rely on proven frameworks to stay disciplined and predictable.
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Radical Candor: We move too fast for politics or sugar-coating. We value direct, honest feedback that helps us find the right answer quickly.
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The Series C Hustle: We have the stability of a well-funded leader but the heart of a startup.
The Perks & Ownership:
We want our team to feel like owners because they are owners. We trust our people to manage their results and their time.
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Meaningful Equity: Every "Safestar" is a shareholder. You aren’t just an employee; you are a partner in our success.
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Unlimited Leaves: We don’t believe in clock-watching. We offer unlimited leave because we trust you to take the time you need to recharge while staying committed to the mission.
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Comprehensive Benefits: We provide top-tier medical insurance and wellness benefits to ensure you and your family are well cared for.
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Career Trajectory: We are growing aggressively. For high-performers, the path for advancement moves at the speed of your ambition.
Key Responsibilities:
Code Mastery: Own feature development and write clean, efficient, maintainable, and production-quality code that drives the product forward.
Technical Contribution: Participate actively in architecture and design discussions and contribute to building scalable, secure, and high-performance solutions.
Code Review: Conduct thorough code reviews to maintain code quality, identify opportunities for improvement, and provide constructive feedback to other engineers.
Cloud Integration: Work with cloud services such as AWS Lambda, API Gateway, EC2, S3, RDS, and other relevant AWS services to build and optimize cloud-based solutions.
Problem Solving: Troubleshoot and resolve complex technical problems by identifying root causes and implementing effective, scalable solutions.
Collaboration: Work closely with product managers, designers, engineers, and other stakeholders to ensure technical solutions are aligned with product and business objectives.
Project Execution: Contribute to project planning and execution and take ownership of delivering features within agreed timelines and scope.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
3–5 years of professional software development experience building scalable backend systems.
Strong proficiency in Go, Python, or Node.js for backend development.
Experience designing and building RESTful APIs and microservices architectures.
Solid understanding of distributed systems concepts such as concurrency, caching, asynchronous processing, and fault tolerance.
Hands-on experience with cloud platforms such as AWS, GCP, or Azure.
Experience building and deploying applications in containerized environments using Docker and Kubernetes.
Strong understanding of SQL and NoSQL databases, including performance optimization techniques.
Experience participating in system design discussions and architecture decisions.
Ability to work effectively in a fast-paced environment with a high degree of ownership.
Strong problem-solving and debugging skills.
Working knowledge of Generative AI and LLM fundamentals, including how LLMs work, tokens, context windows, prompting, hallucinations, and common limitations.
Hands-on experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, or equivalent, with the ability to critically review and validate AI-generated code.
Basic understanding of building applications using LLM APIs, including prompting, structured outputs, and tool/function calling.
Understanding of how to evaluate AI/LLM outputs using appropriate datasets and metrics, and how to measure accuracy and detect regressions rather than relying only on subjective evaluation.
