Software Systems Engineer - Modern AI

The role is primarily about modern AI implementation: connecting models, tools, workflows, data and applications into useful systems. You should be comfortable modifying code, integrating APIs, compiling or configuring software when needed, and translating business requirements into practical technical solutions.

• Comfort setting up and troubleshooting the environments required to run modern AI applications.
• Working knowledge of deployment, environments, APIs, databases and application configuration.
• Comfort with development environments, Git and command-line tooling.
• Ability to trace problems across applications, integrations, data and runtime environments.

• Practical programming ability in at least one current programming language.
• Comfort modifying existing code when configuration or prompts alone are not enough.
• Ability to configure, build/compile and deploy software when required.
• Git/version-control familiarity and disciplined technical changes.

• Hands-on interest in building modern AI-enabled systems and agentic workflows.
• Practical experience with automation/orchestration is strongly preferred.
• Experience with tools such as n8n, LangGraph, vector databases/stores, model APIs, agent frameworks or similar modern AI tooling is strongly valued.
• You do not need to know every AI framework; depth in a few relevant tools and the ability to learn quickly matter more.

You will sometimes start from a business requirement rather than a clean technical specification. The ability to ask the right questions and build a workable setup is important.

AI tooling is moving quickly. We need someone who actively experiments with new models, agentic tools and automation approaches and can decide what is useful rather than simply collecting tools.

Send your resume and a short summary of the AI systems, automations, software or agentic workflows you have built or modified.