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In This Role, You Will
- Design and implement backend services and APIs that are secure, scalable, and maintainable, primarily using Python.
- Work closely with researchers, security engineers, and product teammates to bring AI-driven features from concept to production.
- Apply best practices for authentication, authorization, encryption, and data protection throughout the stack.
- Integrate and optimize advanced AI/ML models within backend architectures.
- Monitor and improve performance, reliability, and resource efficiency to support growth.
- Participate in code reviews, testing, and deployment processes to maintain high standards of quality and security.
- Bring deep experience in cybersecurity, threat detection, or a related area.
- Thrive in fast-moving, high-impact environments, such as startups, AI research labs, or security-focused teams.
- Enjoy tackling complex, ambiguous problems and can adapt quickly as priorities evolve.
- Take initiative, communicate openly, and consistently push yourself — and your team — to deliver exceptional results.
- Work effectively both independently and collaboratively, contributing to team goals while managing your own projects with initiative and accountability.
- Degree in Computer Science, Engineering, or related field — or equivalent professional experience.
- 3+ years of hands-on backend development in production environments.
- Proficiency in backend programming languages such as Python, Java, Kotlin, Node.js, or Go and experience building secure systems, APIs, and microservices.
- Strong understanding of security best practices, including authentication methods (OAuth, JWT), encryption, and secure API development; knowledge of common attack vectors (SQL injection, privilege escalation, DDoS) and effective mitigation strategies.
- Experience integrating and optimizing AI models (e.g., NLP, vision, multimodal systems) within backend services.
- Familiarity with SQL and NoSQL databases; experience with secure data management.
- Experience with cloud infrastructure (AWS, GCP) and secure deployment practices, including containerization (Docker, Kubernetes).
- Experience effectively communicating complex engineering topics to both technical and non-technical stakeholders.
- Familiarity with modern DevOps practices, including test automation, CI/CD pipelines, and infrastructure-as-code practices.
- Salary Range: $105K–$125K, depending on experience and location
- Bonus: Performance-based annual bonus
- Professional Development: Support for conferences, continuing education, or leadership training
- Work Environment: Fully remote, U.S.-based
- Health Benefits: Comprehensive health, dental, and vision coverage
- Time Off: Generous PTO and paid holiday schedule
- Retirement: 401(k) plan
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