QAD, Inc.

QAD, Inc.

Software Engineer, AI Agent Platform

US • Full TimeRemotePosted Today
Full TimeRemote

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Job Description

Company DescriptionRedzone 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-li

Key Highlights

  • 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
  • Support BU Applied AI engineers in building, deploying, and operating Champions correctly

Qualifications

Required Qualifications

  • 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.
  • 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.

Preferred Qualifications

  • 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.

Skills & Technologies

PythonFastAPIReactDockerPostgreSQLGitAWSTerraform

About the Company

QAD, Inc.

QAD, Inc.

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Job Details

Employment Type

Full Time

Location

US • Full Time

Work Mode

Remote

Posted

Today