Agentic AI & Java Engineer for Multi-Agent Workflows

Systematic; Aarhus; On-site; DKK 900,000 - 1,200,000; Full time

Benefits offered by this job

Travel days

Job summary

Systematic in Copenhagen is seeking a Software Engineer to join the Agentic AI team for SitaWare Insight, blending Java and Python with AI to design multi-agent workflows. You’ll implement AI agents, contribute to RAG pipelines, and ensure traceability while keeping humans in the loop.

You’ll collaborate with architects, testers, and product stakeholders across Denmark, delivering production-grade code with strong testing, logging, and observability practices in a security-conscious environment.

Qualifications

• Backend development experience in Java or similar.
• Frontend development experience in Angular or similar.
• Familiarity with Docker and Kubernetes.
• Understanding of microservices and message queues.
• Solid software engineering practices: testing, logging, observability, and version control.

Responsibilities

• Designing and documenting AI agents, tool definitions, and RAG pipelines that connect agents to internal structured and unstructured data
• Building multi‑agent sets using orchestration patterns such as routing, delegation, and result aggregation
• Writing production‑grade code with full test coverage, structured logging, and robust error handling
• Collaborating with domain experts to translate customer journeys into agent task decompositions and evaluation rubrics.

Skills

Java

Angular

Docker

Kubernetes

Microservices

Message queues

Testing

Logging

Version control

LLM/AI systems

Tools

Angular

Docker

Kubernetes

Job description

Systematic in Copenhagen is seeking a Software Engineer to join the Agentic AI team for SitaWare Insight, blending Java and Python with AI to design multi-agent workflows. You’ll implement AI agents, contribute to RAG pipelines, and ensure traceability while keeping humans in the loop.

You’ll collaborate with architects, testers, and product stakeholders across Denmark, delivering production-grade code with strong testing, logging, and observability practices in a security-conscious environment.