Design and implement highly reliable, distributed, backend services and APIs that are secure, scalable, and maintainable, primarily using Python and Kotlin;
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;
Deploy and manage services on Google Cloud Platform (GCP) such as Cloud Run, Vertex AI, and API Gateway with an emphasis on ensuring scalability, reliability, and efficient resource utilization;
Participate in code reviews, testing, and deployment processes to maintain high standards of quality and security; and
Drive other critical initiatives.

You might excel in this role if you:

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; and
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 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
Experience designing and building end-to-end backend systems, from architecture and data modeling to deployment, scaling, and monitoring

Nice to Have:

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

Compensation & Benefits:

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

Software Engineer, Backend

Description