# Software Engineer, AI Agent Platform Remote from[Mexico](https://jobicy.com/job-region/mexico.md)Annual salary Undisclosed Salary information is not provided for this position. Check our [Salary Directory](https://jobicy.com/salaries.md) to estimate the average compensation for similar roles.Department [Software Engineering](https://jobicy.com/categories/engineering.md) Employment type Full Time, Job posted24 Jun 2026Apply before24 Jul 2026Views / Applies 1589 / 113 [About company](https://jobicy.com/company/qad-inc.md) * Share About [QAD, Inc.](https://jobicy.com/company/qad-inc.md) QAD is a leading provider of next-generation manufacturing and supply chain solutions in the cloud. [Computer Software](https://jobicy.com/company-category/software.md) * 1979 Actively Hiring Verified job posting This job post has been [manually reviewed](https://jobicy.com/tools/help-center/employee/how-does-jobicy-verify-the-legitimacy-of-remote-job-listings.md) for authenticity and compliance. ### AI Summary This is a fully remote Software Engineer role on the ChampionAI agentic platform team at QAD | Redzone. The engineer will build platform capabilities, support Applied AI teams, and develop agents for manufacturing use cases. Key responsibilities include developing features in Python with FastAPI, improving developer tooling, and ensuring prompt quality and deployment reliability. The role requires expertise in async Python, prompt engineering, MCP, and agent evaluation. The position follows trunk-based development with TDD and small PRs. ### Role DNA Job Complexity Easy Hard Pace & Pressure Relaxed Fast-paced Autonomy Level Guided Full Ownership Communication Load Independent Highly Collaborative AI Insight This role demands deep expertise in Python, agentic frameworks, MCP, and prompt engineering, along with the ability to support multiple teams. The technical breadth and the expectation of TDD and small PRs make it challenging, hence a 4. ### Salary Analysis Median Market Rate $165,000US Market $120k – 220k 0 $242k AI Insight No salary was specified in the job listing. Based on US market data for senior AI/agent engineers, the estimated median is $165,000. This is competitive for a remote role in the AI platform space. ### Core Skills Required [Python](https://jobicy.com/jobs?search_keywords=Python.md) [FastAPI](https://jobicy.com/jobs?search_keywords=FastAPI.md) [MCP](https://jobicy.com/jobs?search_keywords=MCP.md) [Prompt Engineering](https://jobicy.com/jobs?search_keywords=Prompt+Engineering.md) [Agentic Frameworks](https://jobicy.com/jobs?search_keywords=Agentic+Frameworks.md) [Docker](https://jobicy.com/jobs?search_keywords=Docker.md) [Kubernetes](https://jobicy.com/jobs?search_keywords=Kubernetes.md) [TDD](https://jobicy.com/jobs?search_keywords=TDD.md) [Async Python](https://jobicy.com/jobs?search_keywords=Async+Python.md) [Agent Evaluation](https://jobicy.com/jobs?search_keywords=Agent+Evaluation.md) ### Cover Letter Sample Dear Hiring Manager, I am writing to express my strong interest in the Software Engineer, AI Agent Platform position at Redzone. With extensive experience in building agentic systems using Python, FastAPI, and MCP, I am excited about the opportunity to contribute to the ChampionAI platform. In my previous role, I developed multi-agent architectures and implemented prompt engineering strategies that improved agent reliability by 30%. I am skilled in TDD, async programming, and CI/CD, and I enjoy collaborating with cross-functional teams to solve complex problems. I particularly admire Redzone's focus on manufacturing efficiency and believe my background in agent orchestration and developer tooling aligns perfectly with this role. Thank you for considering my application. I look forward to the possibility of contributing to your team. Copy ### Sample Interview Questions Explain Model Context Protocol (MCP) and how you have used it in a project.MCP is a protocol for managing context between agents and tools. In a project, I built an MCP server that exposed database queries as tools. The server used JSON-RPC to handle tool calls, and agents could discover and invoke them dynamically.How do you approach prompt engineering for production systems?I use XML-structured prompts with clear scope enforcement and tool descriptions. I iterate based on eval results, testing for correctness, scope adherence, and regression. I also use LaunchDarkly to roll out prompt changes gradually.Describe a multi-agent architecture you have implemented and why you chose that pattern.I implemented a supervisor/worker pattern where a supervisor agent delegates tasks to specialist agents. This was chosen to modularize functionality and improve scalability, as each agent could be optimized independently.How do you ensure quality and correctness in agent behavior?I design eval suites using DeepEval for automated checks, including correctness and scope enforcement tests. I also perform manual reviews of agent runs and use regression testing to catch regressions after prompt updates.How do you support other engineers in building agents on a platform?I provide clear documentation, scaffolding tools, and onboarding guides. I pair with engineers on first deployments, review their implementations, and maintain internal libraries to abstract common patterns. ## Company Description Redzone is the #1 Connected Workforce Solution for manufacturers big and small. We work to improve efficiency in plants, provide coaching for best practices, and enable the front-line worker to improve the quality of their work and their work life by providing them with tools, processes, and collaboration tools to keep their manufacturing lines running smoothly and efficiently. At Redzone we focus on the customer experience, listening to the customer, and providing solutions that create great outcomes. We are a combination of great leadership, years of manufacturing experience, and an incredible technology team that all work together to create great products. This role is fully remote. ## Job Description ChampionAI is QAD | Redzone agentic platform, purpose-built for manufacturing and utilized by the various business units within QAD | Redzone. This engineer joins the core platform team with three main areas of focus: building new capabilities into the platform, helping Applied AI teams at partner business units build and ship Champions correctly, and directly building Champion agents for business-unit use cases when needed. You will work in the same codebase as the Applied AI engineers you support, which keeps the enablement work practical and the platform work focused on real problems. Key Responsibilities Platform Development * Build and ship features across the Champion platform repositories * Improve developer experience: tooling, scaffolding, internal documentation, and onboarding paths for Applied AI engineers. * Maintain and evolve the MCP tool server and agent infrastructure that BU teams depend on. * Identify and address friction points that slow down Champion development or deployment Applied AI Enablement * 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 Agent Development * 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 * Register agents in Champion Server and configure LaunchDarkly-gated prompt rollout across environments Engineering Practices We follow trunk-based development with PR-gated merges to main. Engineers are expected to: * Write tests before implementing. TDD is the expectation, not a nice-to-have. * Keep PRs small and focused; use feature flags to ship partial work incrementally * Follow conventional commit format (feat:, fix:, etc.) * Be mindful of API and schema backward-compatibility; prefer additive changes over breaking ones * Review your own diff before requesting review ## Qualifications Core Requirements * Python: Proficient in async Python, Pydantic, type hints, and FastAPI. Experience with the Strands agent SDK or a comparable agentic framework. Testing is non-optional: candidates should be comfortable with pytest, pytest- asyncio, and DeepEval for agent-specific evaluation. We test agent behavior, not just unit logic. * Prompt Engineering: Able to write and iterate on production system prompts: XML-structured, scope-enforced, with tool descriptions that guide LLM delegation reliably. * Model Context Protocol (MCP): Solid understanding of MCP and hands-on experience building or consuming MCP servers. Familiarity with Agent-to-Agent (A2A) protocol is a strong plus. * Agent Patterns: Familiar with multi-agent architectures and orchestration patterns beyond basic ReAct: supervisor/subagent delegation, parallel tool use, handoffs, and context management across agent boundaries. * Agent Evals: Able to design and run evaluation suites for agent behavior: correctness checks, scope enforcement tests, regression coverage, and systematic prompt iteration based on eval results. * Docker: Comfortable authoring Dockerfiles, multi-stage builds, and local dev environments via docker-compose / make. * PostgreSQL: Comfortable with templated INSERT/SELECT, foreign key relationships, and reading an ER diagram. * Git / Semantic Versioning: Follows conventional commit format (feat:, fix:) and a PR-based trunk workflow. Nice to Have * Kubernetes: Working knowledge of Deployments, Services, ConfigMaps, and ServiceAccounts. Able to read and adapt K8s manifests and use kubectl for basic troubleshooting. * AWS: Working knowledge of ECR, EKS, IAM, and Bedrock (inference layer). * OAuth2 / OIDC: Conceptual understanding of Authorization Code Flow with PKCE, token exchange, and agent auth delegation. * Terraform: Beginner-level familiarity; able to make targeted changes to existing modules and interpret a plan diff. * LaunchDarkly: Experience managing feature flags or AI config overrides for environment-gated rollout. * Document Intelligence / OCR: AWS Textract or comparable pipeline experience for use cases involving structured document extraction. AI-Native Development * We run an AI-native SDLC. AI-assisted tools (Claude Code, Cursor) are part of the standard engineering workflow at every stage: planning, implementation, review, and documentation. This is not optional or supplemental; it is how we work. Candidates should be comfortable with AI-assisted development and willing to invest in getting good at it. * Use Claude Code and Cursor actively across planning, implementation, and code review * Know when AI output is wrong and push back on it. * Help drive adoption across the team by sharing what works What This Role Is Not This is not an ML research or data science role. The platform team owns cluster networking, observability pipelines, auth configuration, and LLM routing, so deep expertise in those areas is not required. The job is building reliable software on top of that infrastructure and helping others do the same. ## Additional Information About QAD: [QAD](https://www.qad.com/) | [Redzone](https://rzsoftware.com/) is redefining manufacturing and supply chains through its intelligent, adaptive platform that connects people, processes, and data into a single System of Action. With three core pillars — Redzone (frontline empowerment), Adaptive Applications (the intelligent backbone), and Champion AI (Agentic AI for manufacturing) — QAD | Redzone helps manufacturers operate with [Champion Pace](https://www.qad.com/champion-pace), achieving measurable productivity, resilience, and growth in just 90 days. QAD is committed to ensuring that every employee feels they work in an environment that values their contributions, respects their unique perspectives and provides opportunities for growth regardless of background. QAD’s DEI program is driving higher levels of diversity, equity and inclusion so that employees can bring their whole self to work. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. #LI-Remote Show more [Apply now >](https://jobicy.com/jobs/147582-software-engineer-ai-agent-platform.md) > Annual salary information is not provided for this position. 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