11 days ago
Paris, France or Singapore, SingaporeMid Level
Responsibilities
- Build, tailor, deploy, and operate AI agents and assistants for internal functions.
- Build and maintain knowledge-base pipelines that support accurate and useful AI systems.
- Integrate AI systems with company tools and data sources through APIs and connectors.
- Apply access control, data privacy, human-in-the-loop safeguards, and responsible-AI practices.
- Build user-facing interfaces and the backend services supporting them.
- Measure adoption, quality, and cost, and improve solutions based on internal-user feedback.
- Maintain reliable, observable, and maintainable systems and participate in incident response and root-cause analysis.
- Create documentation and runbooks and contribute to shared frameworks and AI-assisted engineering practices.
Requirements
- At least 3 years of professional engineering experience.
- Experience building and operating production systems end-to-end, including services, APIs, or tooling.
- Hands-on experience building with LLMs, including features, agents, automations, or production-quality side projects.
- Understanding of system design, databases, data modeling, and application architecture.
- Proficiency in Python and/or TypeScript.
- Experience with LLM application development, model APIs, prompt/context engineering, and basic RAG patterns.
- Experience with API design, data integration, database design, SQL, and data modeling.
- Familiarity with cloud infrastructure, AWS, Docker, Kubernetes, and CI/CD practices.
- Strong problem-solving, collaboration, and user-centric skills.
- Desirable: experience with agent frameworks, MCP-style tool interfaces, RAG, knowledge-base systems, third-party SaaS APIs, full-stack development, internal or developer-facing tools, LLM evaluation, or observability.
Tech Stack
Categories
