[Hiring] Software Engineer, AI Agent Platform @QAD, Inc.

Role Description

This role is based in Mexico & fully remote. Work authorization required; we do not offer visa sponsorship.

ChampionAI is QAD | Redzone's agentic platform, purpose-built for manufacturing and utilized by 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.
• 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.

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.
• 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.

Requirements

• 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.

Benefits

• Full-time position.
• Remote work opportunity.
• Compensation: MXN 55,000 - MXN 85,000 monthly.