Overview
The AI Engineer is responsible for designing and maintaining scalable, high-performance backend systems that power AI and LLM-driven workflows.
This role is deeply technical, focused on building robust data layers, APIs, and agent orchestration logic.
The ideal candidate brings strong experience with modern Python tooling, backend architecture, and hands-on knowledge of AI workflows, ensuring seamless integration between data models, business logic, and AI systems.
Responsibilities
- Develop and maintain scalable backend systems using Python
- Design, model, and optimize the data layer using SQLModel and PostgreSQL
- Build GraphQL APIs to serve internal and external clients
- Integrate and orchestrate AI agents and workflows using LangGraph and related tools
- Structure and validate business logic using Pydantic and other typed schema libraries
- Collaborate with the product and frontend teams to shape features end-to-end
- Contribute to architectural decisions and long-term technical strategy
- Engage proactively in async communications, code reviews, and architecture discussions
Requirements
- Strong experience with Python and modern Python tooling
- Experience designing APIs and backend systems using GraphQL (ideally with Strawberry)
- Deep familiarity with Pydantic or similar data validation frameworks
- Hands-on experience with SQLModel, SQLAlchemy, or equivalent ORM tools
- Proficiency in relational databases and async programming in Python
- Comfort working with AI/LLM workflows and agentic design patterns (LangGraph or similar)
- Solid understanding of backend architecture, observability, and performance optimization
- Fluent in English
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