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CLAR AI

Converts conversations into executable workflows

Fullstack AI Engineer

Full-Stack EngineeringConfirmed live in the last 24 hours
Full-timeMunich, Germany

About the Job

Requirements

  • Have strong software engineering foundations and write clean, production-ready code.
  • Be comfortable building full-stack web applications, including with React, TypeScript, and Node.js or Python.
  • Be able to build performant frontends and backend logic.
  • Work across data flows, APIs, user interfaces, and deployment and operations.
  • Understand how relational data structures and component architecture shape product experience.
  • Have built and owned features end-to-end.
  • Understand where AI is appropriate and how to build on foundation models, retrieval, voice AI, multi-agent architectures, and external tools.
  • Be able to develop reusable platform systems through clear, composable code.

Responsibilities

  • Design and develop frontend and backend software features, establish technology stack choices and API standards, and contribute to the agentic platform.
  • Build customer-facing features with Forward Deployed Engineers, covering database models, APIs, and user interface components.
  • Design and build human-in-the-loop controls, monitors, and configuration surfaces for AI agents.
  • Integrate large language model inference, retrieval, tool and agent orchestration, and evaluations to launch and productionize AI integrations into the platform.
  • Design backend services and typed interfaces with observability and continuous integration and continuous delivery.
  • Build robust connectors into customer systems that support agentic logic and frontend experiences.
  • Evolve the design system, shared repositories, and developer tooling by turning one-off solutions into libraries, patterns, and platform primitives.
  • Contribute to shaping the product roadmap and the company's technical direction.

About the Company

CLAR AI

Converts conversations into executable workflows

CLAR AI automates enterprise workflows by turning everyday conversations into actions executed inside a company’s existing systems, including tasks like updating records and completing processes, through channels employees and customers already use (voice, email, WhatsApp, Teams). Its product uses agentic AI to understand a business context by modeling products, customers, processes, and rules, so the AI can act like an experienced colleague. A governance layer checks actions against standard operating procedures, enforces user roles, and allows human oversight when needed, ensuring consistent, compliant execution without a new user interface. The goal is to scale repetitive requests, improve data quality from conversations, and boost operational efficiency and customer satisfaction while staying within the current software stack.

Company size
1-10
Company stage
Not listed
Total funding
Not listed
Headquarters
Munich, Germany
Founded
2026

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