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AI Software Engineer
Job description
At konversaitional, we transform business processes into natural conversations. Our AI agents execute tasks — they don’t just answer questions. They act as virtual employees and connect to ERP/CRM systems, all without the client needing IT involvement.
Our company is rapidly expanding and offers you a challenging work environment is the fast-moving AI landscape. As an employee of our tech startup, you will collaborate with each department to create and deploy disruptive products.
As our AI Software Engineer, you build the platform that makes all of this possible. Think of yourself as the architect and builder of a theatre: the AI Project Engineers put on the show, but you design the stage, the lighting system, and the trapdoors that make the magic happen. Without your work, there is no show.
You own two things: the agent platform itself (the engine under the hood) and the front-end interfaces clients and end-users actually interact with.
What you’ll build
The agent platform
- Design and develop the core infrastructure that runs our AI agent teams
- Build orchestration logic: how agents are triggered, how they hand off to each other, how they recover from errors
- Ensure the platform is model-agnostic — swapping or upgrading the underlying AI model should never mean rebuilding from scratch
- Build and maintain the integration layer that connects agents to client systems (ERP, CRM, ticketing, case management)
- Think in reliability, scalability and security from day one — our clients run mission-critical processes on this
Front-end and chat interfaces
- Build the conversational interfaces through which end-users interact with agents (web chat, embedded widgets, Teams)
- Translate complex agent behaviour into experiences that feel simple and human
- Work closely with the AI Project Engineers to understand what clients need and make it real
- Ensure interfaces are fast, accessible and easy to configure per client deployment
Platform quality and evolution
- Write clean, maintainable code — you’re building something that will grow fast
- Set up and maintain CI/CD pipelines and deployment processes
- Monitor platform performance and proactively address bottlenecks
- Stay close to the rapidly evolving AI tooling landscape — and bring the best of it into the platform
Profile
Your profile
Must-haves
- 3–6 years of experience building production-grade software
- Solid full-stack skills: comfortable with both backend logic and building polished front-end experiences
- You’ve worked with APIs and know what good integration architecture looks like
- You understand AI/LLM concepts well enough to build systems around them — you don’t need to train models, but you need to orchestrate them effectively
- You write code others can read, maintain and build on
- You’re pragmatic: you know when to build the elegant solution and when to ship something that works
Nice-to-haves
- Experience with conversational UI or chat-based interfaces
- Familiarity with agent frameworks or LLM orchestration tools
- Experience building multi-tenant SaaS platforms
- Knowledge of MCP (Model Context Protocol) or similar integration standards
- You’ve worked in an early-stage startup before and know what that pace feels like
Offer
What's great in the job?
- Great team of smart people, in a friendly and open culture
- No dumb managers, no stupid tools to use, no rigid working hours
- No waste of time in enterprise processes, real responsibilities and autonomy
- Expand your knowledge of various business industries
- Create content that will help our users on a daily basis
- Real responsibilities and challenges in a fast evolving company
What We Offer
- A fast-moving, challenging tech startup environment
- A competitieve salary package tailored to your knowledge and experience
- Flexible home working policy
- Direct collaboration with the founder and 3 software colleagues — short lines, fast decisions
- Enjoy the fast-paced work environment of an ambitious tech startup
- 32 vacations days, free to take, as you like
- Room to grow as konversaitional scales
- Permanent employment
Tech stack
We are deliberately keeping our stack choices open — we want the right person to help shape them. We care more about engineering fundamentals and sound architectural thinking than specific framework preferences.
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