QA Engineer – Edge AI & Perception Pipelines

About CraftifAI

At CraftifAI, we're building PipeGen under CraftifAI Orbit—an AI-native, multi-agent development platform that helps engineering teams build, optimize, and deploy production-ready perception pipelines for edge devices.

PipeGen combines AI agents, model optimization, compiler technologies, deployment automation, and validation workflows to transform natural language requirements and trained AI models into deployable Edge AI applications.

We're looking for a QA Engineer who wants to go beyond traditional software testing and help validate the next generation of AI-powered developer tools.

About the Role

As an AI Platform QA Engineer, you'll validate the quality, reliability, and correctness of PipeGen across the complete AI deployment lifecycle—from user prompts and AI-generated pipeline designs to model deployment, runtime behavior, and generated project artifacts.

You'll work closely with AI, platform, deployment, and product engineering teams to ensure PipeGen consistently generates reliable, deployable, and production-ready Edge AI solutions.

This role is ideal for engineers who enjoy testing complex technical systems, analyzing AI-generated outputs, validating deployment workflows, and improving product quality through automation and systematic testing.

What You'll Do

• Test PipeGen's end-to-end workflows, from user prompts and requirement generation to pipeline creation, model deployment, execution, and validation.
• Validate AI-generated pipeline architectures, generated code, configuration files, deployment artifacts, documentation, and runtime behavior.
• Design test scenarios covering diverse Computer Vision and Edge AI use cases, including object detection, segmentation, classification, depth estimation, and video analytics.
• Verify model deployment workflows, build outputs, runtime execution, logs, benchmark results, and generated reports across supported edge platforms.
• Perform regression, functional, integration, and exploratory testing across AI models, prompt variations, hardware targets, and product releases.
• Identify, reproduce, and document issues related to AI-generated outputs, deployment workflows, build failures, runtime behavior, configuration errors, and model compatibility.
• Validate AI agent behavior across different prompts, deployment scenarios, and recovery paths to ensure reliable and consistent outputs.
• Collaborate with AI researchers, developers, and product teams to improve quality, validation strategies, release readiness, and overall user experience.

Required Skills

• 1–3 years of experience in Software QA, AI platform testing, developer tools, ML systems, Edge AI, or related technical products.
• Strong understanding of software testing principles, test planning, regression testing, exploratory testing, defect reporting, and release validation.
• Experience testing complex applications involving UI, backend services, generated files, logs, APIs, or runtime workflows.
• Ability to analyze logs, build outputs, runtime errors, generated artifacts, and AI-generated results to identify defects and inconsistencies.
• Basic understanding of AI model deployment, inference workflows, Computer Vision, or Edge AI applications.
• Strong analytical and problem-solving skills with excellent written communication.
• Familiarity with Python, Linux, Git, or scripting for testing and debugging is desirable.

Nice to Have

• Experience testing AI platforms, developer tools, ML deployment systems, or Computer Vision applications.
• Familiarity with Edge AI technologies such as ONNX, TensorRT, DeepStream, GStreamer, CUDA, NVIDIA Jetson, or similar deployment ecosystems.
• Experience with QA tools such as Jira, GitHub Issues, TestRail, Postman, CI/CD pipelines, or test automation frameworks.
• Exposure to AI agents, LLM-based products, prompt testing, RAG systems, or AI output evaluation.
• Familiarity with robotics, perception systems, sensor fusion, or embedded Edge AI platforms is a plus.

Why Join CraftifAI?

At CraftifAI, you'll help build the quality foundation of PipeGen, an AI-native platform that's transforming how Edge AI perception pipelines are designed, optimized, and deployed.

You'll work on a technically challenging product that combines AI agents, Computer Vision, Edge AI, model deployment, compiler technologies, and intelligent automation—giving you the opportunity to shape the quality of next-generation AI developer tools rather than testing traditional business applications.

If you're excited about AI, Edge AI, Computer Vision, developer platforms, and building reliable AI-powered products, we'd love to hear from you.