Overview

Organization OverviewCompany Description

Responsibilities

• QAD | Redzone is redefining manufacturing and supply chains through an intelligent, adaptive platform that connects people, processes, and technology into a single System of Action. Founded in 1979 and headquartered in Miami, Florida, the company serves manufacturers across more than 100 countries in industries including automotive, consumer products, food and beverage, high technology, industrial equipment, and life sciences.
• The platform is built on three core pillars: Redzone (frontline empowerment), Adaptive ERP (the intelligent backbone of manufacturing operations), and ChampionAI (Agentic AI purpose-built for manufacturing). Together, these enable manufacturers to achieve measurable productivity, resilience, and growth — in as little as 90 days.
• ChampionAI is QAD | Redzone's agentic platform, purpose-built for manufacturing and used across all business units. As a junior-level Engineer, you will join the core platform team to build new platform capabilities, help Applied AI teams ship Champion agents correctly, and directly build Champion agents for business-unit use cases.
• Build and ship features across the Champion platform repositories using trunk-based development with PR-gated merges.
• Improve developer experience through tooling, scaffolding, internal documentation, and onboarding paths for Applied AI engineers.
• Maintain and evolve the MCP tool server and agent infrastructure that business unit teams depend on.
• Identify and address friction points that slow down Champion development or deployment.
• Support BU Applied AI engineers in building, deploying, and operating Champions correctly.
• Review agent implementations for prompt quality, scope enforcement, auth configuration, and deployment setup.
• Contribute to internal engineering guides and skill documentation.
• Pair with BU engineers on first K8S manifest creation, database registration, and LaunchDarkly prompt rollout.
• Design and build Champion agents for BU use-cases when the platform team is directly engaged.
• Write and iterate on system prompts, tool bindings, and context injection for production agents.

Qualifications

• 2+ years of hands-on software development experience, specialising in Python, Golang and AI-driven systems.
• Proficiency in Python (async, FastAPI, Pydantic, pytest, pytest-asyncio, DeepEval), Docker, PostgreSQL, and Git.
• Good understanding of Model Context Protocol (MCP), Agent-to-Agent (A2A) protocol, and multi-agent architectures.
• Familiarity with LaunchDarkly and AI-native development tools (Cursor, Claude Code).
• pytest
• FastAPI
• Docker
• PostgreSQL
• A2A
• Multi-agent Patterns
• Tool Bindings
• pytest-asyncio
• Monitoring
• Logging
• Claude Code
• LaunchDarkly
• Git

Nice to have

• Working knowledge of AWS (ECR, EKS, Bedrock), Kubernetes, and Terraform.
• M.S. / M.Tech in Computer Science, AI, or ML.
• Exposure to manufacturing or industrial software contexts.

Education

• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• M.S. / M.Tech in Computer Science or AI/ML is a plus.
• Your health and well being are important to us at QAD. We provide programs that help you strike a healthy work-life balance.
• Opportunity to join a growing business, launching into its next phase of expansion and transformation.
• Collaborative culture of smart and hard-working people who support one another to get the job done.
• An atmosphere of growth and opportunity, where idea-sharing is always prioritized over level or hierarchy.
• Compensation packages based on experience and desired skill set