Clera
AI & Backend Engineer
About this role
Join a lean B2B SaaS startup building AI-powered customer support agents that autonomously resolve enterprise tickets. As an AI & Backend Engineer, you'll own full-stack features end-to-end, designing intelligent agent pipelines and scaling the infrastructure that powers them in a hands-on role at a sub-15 person company.
What you'll do
- Design and ship full-stack product features from conception through production deployment
- Build AI-powered capabilities including LLM integrations, prompt engineering, and agent orchestration pipelines
- Develop and maintain backend systems using Python and FastAPI to support agent operations
- Collaborate with product and engineering teams to plan, scope, and launch new agent features
- Optimize internal development workflows by integrating AI coding tools into team practices
- Manage database architectures using PostgreSQL and Firestore for scalable data operations
What they're looking for
- Backend engineering (Python, FastAPI)
- LLM integration and prompt engineering
- AI agent design and implementation
- Full-stack development (TypeScript, React, Next.js)
- Relational and NoSQL databases (PostgreSQL, Firestore)
- Infrastructure and DevOps (Docker, Kubernetes, GCP)
- System architecture design
- AI coding tools and workflows
Benefits
- Visa sponsorship available
- Direct impact on product direction and strategy
- High ownership and autonomy in a small team
- Hands-on work with cutting-edge AI models
- Collaborative environment with rapid iteration cycles
- On-site collaboration in Munich for team cohesion
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Clera
Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.
View all jobs at CleraLikely interview questions
- Walk us through a backend system or AI feature you shipped to production—what was your architectural approach and what challenges did you solve?
- Tell us about a personal project involving LLMs or AI that demonstrates your curiosity in this space.