Job
In this role, you will develop AI systems, design agent architectures, and integrate ML concepts into a SaaS application while also managing and optimizing their operations.
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Your role in the team
- You develop our AI systems - from agent-based assistants to a platform where our clients can assemble their own agents, tasks, and workflows.
- The role is hands-on: You write code, design agent architectures, and also operate what you build yourself.
- In this role, you work at the point where it is decided whether an AI feature impresses only in the demo or functions reliably in the daily operations of our clients.
- You work closely with backend development, product, and [other interfaces], actively contributing your insights to architecture and product decisions.
- (Further) development of our agent-based AI assistant - from conception through implementation to operation.
- Co-developing a dynamic multi-agent system in which customers can create and configure their own agents, tasks, and workflows.
- Design of agent systems whose behavior and quality are controllable and traceable - including guardrails, permission concepts, and human-in-the-loop mechanisms.
- Development of systematic evaluation strategies: You verify whether changes to prompts, tools, and agents are genuinely improvements — not just perceived as better.
- Integration of AI and ML concepts into an existing, mature SaaS application - including everything that comes with it: data model, permissions, performance, costs.
- Operations and Optimization: Observability, Tracing, Latency, Cost, and Stability Optimization.
Our expectations of you
Qualifications
- Very good conceptual understanding of how LLMs work — and their limitations.
- Understanding further ML concepts and how to meaningfully integrate them into business logic.
- In-depth understanding of tokenization/tokens, embeddings, and context windows.
- Understanding of Vector Search, Retrieval, and Re-ranking (RAG).
- Knowledge of hallucinations, context bloat, and other common error modes – including strategies to identify and mitigate them.
- Understanding of A2A (Agent2Agent Protocol), MCP (Model Context Protocol), and Human-in-the-Loop.
- Knowledge of security risks of LLM and agent systems (including prompt injection, tool misuse, data leakage).
- Understanding Context Engineering - targeted selection, preparation, and management of what actually enters the Context Window.
- Understanding of multi-agent architectures, agent handoffs, and orchestration (A2A).
- Ability to develop systematic evaluation strategies for agents and other ML components.
- Understanding of quality metrics and evaluation methods - e.g., LLM-as-a-Judge, Task Success Rate, Tool Call Accuracy.
- Testing and versioning of agents, prompts, and tool definitions.
- Optimization of quality, stability, latency, and costs.
- Genuine interest in testing and deploying various AI and ML concepts within an existing SaaS application.
- Pragmatism: You know the difference between an impressive demo and a system that still does the right thing even on the 10,000th run.
Experience
- Experience with Tool Calling and Structured Outputs.
- Experience in Prompt Engineering - formulation, structure, and management of individual model requests.
- Experience in Harness Engineering - designing the environment in which an agent operates: tools, feedback loops, control flow, and termination conditions.
- Experience with guardrails and permissions, especially RBAC and ABAC in user-centric SaaS systems.
- Experience or solid understanding of asynchronous processing, background jobs, and task queues.
What we offer
- There is the possibility to work remotely, hybrid, or on-site.
- Structured onboarding into the product, processes, and testing procedures.
Topics you will work on
Job locations
About your employer
conmeet GmbH, based in Borken, Germany, is a modern company focused on developing digital control system solutions for craft and construction businesses. Their cloud-based software platform integrates various business processes such as order processing, project management, and controlling, primarily targeting medium-sized companies. Since its founding in 2023, the company has been enhancing its platform with AI-driven features to meet industry demands.
- Startup
- Onsite, Hybrid
- Construction, Real Estate, Building Services
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