Principal Engineer managing authentication services at Menlo Security. Leading a team to optimize security and performance in systems programming with Rust or Go.
About the role
- Backend Developer focused on designing and evolving backend infrastructure for AI products. Collaborating with engineering teams to deliver reliable, scalable services and features.
Responsibilities
- Design, develop, and maintain scalable RESTful/GraphQL APIs and microservices for our AI chatbot and other backend systems
- Implement multi-agent AI systems using frameworks such as LangChain/LangGraph (or equivalent): multi-agent orchestration, tool calls to external APIs, reasoning loops, and memory/state management
- Integrate third-party LLM providers and manage prompt engineering, rate limiting, cost optimization, and fallback logic
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines: document ingestion, embedding generation, vector search/retrieval, and contextual response generation
- Work with traditional databases and modern vector databases. Build and maintain reliable integrations with external services via APIs, webhooks, and event-driven patterns
- Ensure high availability, performance, security, observability, and scalability of all backend services (monitoring, logging, caching, asynchronous processing)
- Write clean, testable, and well-documented code; actively participate in code reviews, architectural discussions, and agile ceremonies
- Collaborate closely with other engineering teams and product stakeholders to deliver end-to-end features.
Requirements
- 5+ years of hands-on backend software development experience
- Strong proficiency in Python and modern Python web frameworks (FastAPI, Django, or Flask strongly preferred)
- Solid understanding of relational and NoSQL databases, ORM/query optimization, and data modeling
- Experience designing and consuming RESTful APIs, GraphQL, or event-driven architectures (Kafka, RabbitMQ, etc.)
- Familiarity with cloud platforms (AWS, GCP, or Azure), including serverless architectures, containers (Docker), and basic orchestration (Kubernetes or equivalent)
- Practical knowledge of AI integration concepts: large language models (LLMs), embeddings, vector search, RAG patterns, and basic tool-calling techniques
- Strong software engineering skills: clean code, testing (unit and integration), CI/CD, Git, and agile methodologies
- Excellent problem-solving skills and the ability to decompose complex AI-related requirements into robust backend solutions
- Proficiency in English communication*. French is a plus.
Benefits
- 4 weeks of vacation + 5 personal days annually
- Group insurance programs starting on your first day, including access to telemedicine and an Employee Assistance Program (EAP)
- Company holiday shutdown
- Group RRSP with employer contributions available from your first day
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