AI Tool Developer
AI Tool Developer
Plano, TX
The AI Tool Development Support will primarily be responsible for collaborating and providing technical support.
Responsibilities:
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Develop an end to end AI model and processing pipeline that transforms natural language or structured test specifications into executable JSON scripts used by internal test automation tool.
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Build prompt driven, rule augmented, or fine tuned models using TMNA approved AI platforms, ensuring compliance with internal AI/ML Review Board standards. Create data ingestion and training datasets using historical test cases, existing automation scripts, and test execution logs.
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Design the mapping framework between spec semantics automation actions JSON schema.
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Build validation utilities to automatically ensure script correctness, schema compliance, and alignment with automation tool capabilities.
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Integrate the AI generation pipeline into the existing test automation toolchain and CI based workflows.
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Collaborate with automation SMEs to refine domain specific rules, edge cases, and test coverage requirements.
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Drive continuous model improvement through error analysis, incremental fine tuning, and user feedback loops.
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Maintain documentation, versioning, and traceability of AI generated scripts.
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Ensure responsible AI usage by aligning with TMNA governance, data handling, and compliance requirements.
Skills Required:
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5+ years of experience building AI/ML or NLP based solutions, including prompt engineering, LLM based workflows, or model fine tuning.
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Solid Python or similar development skills (data processing, model building, evaluation pipelines).
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Experience working with JSON schema design and automated test frameworks.
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Familiarity with ML frameworks such as PyTorch, TensorFlow, HuggingFace or similar libraries.
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Experience with building or integrating ML pipelines into production quality tools (API services, microservices, or batch systems).
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Strong understanding of software testing concepts: test cases, assertions, conditions, flows, automation logic.
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Ability to collaborate with cross functional engineering teams and translate ambiguous test definitions into structured logic.
Educational Background:
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Bachelor's Degree (or higher) in Computer Science, Management Information Systems or related discipline, or equivalent professional work experience
Added Bonus:
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Experience with automated test frameworks used in embedded or multimedia systems.
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Experience with model fine tuning using enterprise datasets.
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Background in building developer tooling, code generation, or compiler/AST type transformations.
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Familiarity with LEAP/MM automation concepts or previous exposure to internal test automation pipelines.
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Experience implementing AI tools in enterprise environments requiring governance and model approval.
