AI-First Software Developer - Softeon

Ship more of what customers need, faster, and prove every change works. 

Our applications run the warehouses that get orders out the door on time. We are changing how that software gets built: AI agents and AI-assisted CI/CD help us deliver more functionality to our customers, faster, with higher quality. 

We are looking for an AI-first developer: someone who treats AI agents as a team to direct, not a fancy autocomplete. You will pair deep Java engineering with hands-on experience building through agents to deliver great new functionality across our applications, and you will help set the standard for how the rest of engineering works this way. You know that speed only counts if it comes with proof, so automated testing, validation and agent-assisted review are part of how you ship every change. 

What you will do 

• Deliver great product functionality. Design and build new features and enhancements across our Java applications (receiving, inventory, picking, replenishment, shipping, integrations and user experience) that customers value and rely on. 
• Build with agents every day. Use Claude Code and similar coding agents to plan, implement, refactor and test features. Break work into clear specs, give agents strong context, and know when to delegate and when to step in. 
• Author and maintain agent skills. Write and refine skills, prompts, tool definitions and MCP servers that encode Softeon's domain knowledge, such as Elastic UI form and flow authoring, WMS configuration and integration patterns. 
• Own a fully automated delivery pipeline. Build and run CI/CD where every change passes automated builds, unit and integration tests, static analysis, security scanning and AI agent code review before a human approves it. 
• Make quality provable. Build and extend automated validation (unit, API and Playwright end-to-end tests) so that AI-generated code, configuration and integrations are verified automatically, with evidence. 
• Operate what you ship. Build the telemetry, logging and monitoring your features need, and treat performance and reliability as product requirements rather than a late pass. 
• Modernize with confidence. Use agents to understand, refactor and modernize existing code, add missing test coverage, and pay down technical debt without slowing feature delivery. 
• Measure velocity and quality. Track cycle time, defect rates and escaped bugs, and use the data to keep improving how agents and pipelines are used. 
• Work with product and customers. Turn real warehouse and supply chain needs into well-specified, testable software, and talk with product managers, customers and Ops teams in their language. 
• Raise the bar for the team. Share patterns, review others' agent workflows, measure what works, and help colleagues become effective AI-first developers. 
Why it is interesting 

• Agents can write code faster than any team can review it. The hard part is no longer typing; it is deciding what to build, giving agents the right context, and proving that what comes back is correct in a domain where a plausible answer can still stop a warehouse. That means designing the specs, skills, tests and pipeline gates that let a small team ship enterprise software at a pace that used to need a much larger one, and there is no settled playbook to copy. 
• You will do this on mature, mission-critical applications with real customers, real data and real operational stakes, which is a harder and more rewarding problem than a greenfield demo. 
Frameworks and tools you will work with:

Languages & core 

• Java 17+, Spring / Spring Boot, REST and messaging APIs, SQL and relational databases 
Front end 

• TypeScript, Angular, and Elastic UI, our metadata-driven UI platform (XSLT forms and flows rendered as JSON schema) 
Scripting & extension 

• Groovy scripts and connectors, extension APIs and scaffolding for customer and partner modifications 
AI & agents 

• Claude Code and other coding agents, agent skills, Model Context Protocol (MCP) servers, LLM APIs, evaluation of agent output 
Quality 

• JUnit, API and integration testing, Playwright end-to-end tests, test data and fixtures, mutation testing 
Delivery & DevSecOps 

• GitHub and GitHub Actions (or Jenkins / Azure DevOps), automated agent code review, static analysis, security scanning, SBOM, Docker, Kubernetes, infrastructure as code 
Operations 

• Logging, telemetry, monitoring and observability tooling across cloud environments

Department: Research and Development
Function: Human Resources
Experience Level: Mid-Senior Level