engineering
Posted Apr 23, 2025Backend Engineer (AI Agents)
at ashby:mazehq
Remote
Responsibilities
- - Architect and Develop: Design and implement backend systems that effectively support agentic workloads, ensuring they are scalable, maintainable, and secure.
- - Integrate Seamlessly: Work closely with other engineers, our designer/product manager to ensure seamless integration of new features and services.
- - Optimize for Performance: Continuously monitor and improve application performance, security, and scalability.
- - Establish Best Practices: Define and enforce coding standards, best practices, and documentation to maintain high code quality.
Requirements
- Summary of the Role: As an Engineer at Maze, you'll play a pivotal role in shaping our product, with significant focus on the development of AI Agents and ML systems.
- You will have the unique opportunity to design, build, and scale a product from the ground up, influencing everything from architecture decisions to ML integrations and the overall user experience.
- This is an exciting chance to be at the core of our technical team, driving innovation in AI-powered cybersecurity solutions and ensuring seamless integration across the stack.
- Your Contributions to Our Journey: - AI Agents: Play a pivotal role in the development and scaling of complex AI Agents to tackle some of the biggest challenges in cybersecurity.
- experience in backend development - Backend Mastery: Strong
- experience with backend development, including RESTful API design, database management, and server-side frameworks (e.g., Python). - ML/AI Understanding: Working knowledge of machine learning principles and
- experience integrating LLMs or other AI services into production applications. Familiarity with tools like LangChain, LlamaIndex, or similar frameworks is a plus. - Cloud
- Experience: Familiarity with cloud platforms (e.g., AWS) and their ML services, along with DevOps practices, including CI/CD and containerization (e.g., Docker, Kubernetes).
- - AI Systems Architecture: Understanding of how to architect systems that effectively leverage AI capabilities while maintaining performance and reliability.
- - Collaborative Spirit: Excellent communication skills and the ability to work effectively in a cross-functional team.
- - Agility and Adaptability: Comfort working in a fast-paced startup environment with the ability to pivot and adapt as needed, particularly in the rapidly evolving AI landscape.