AI Tool Developer

AI Tool Developer
Plano, TX

The AI Tool Development Support will primarily be responsible for collaborating and providing technical support.


Responsibilities:

• 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.

• 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.

• Design the mapping framework between spec semantics → automation actions → JSON schema.

• Build validation utilities to automatically ensure script correctness, schema compliance, and alignment with automation tool capabilities.

• Integrate the AI generation pipeline into the existing test automation toolchain and CI-based workflows.

• Collaborate with automation SMEs to refine domain-specific rules, edge cases, and test coverage requirements.

• Drive continuous model improvement through error analysis, incremental fine-tuning, and user feedback loops.

• Maintain documentation, versioning, and traceability of AI-generated scripts.

• Ensure responsible AI usage by aligning with TMNA governance, data-handling, and compliance requirements.

Skills Required:

• 5+ years of experience building AI/ML or NLP-based solutions, including prompt engineering, LLM-based workflows, or model fine-tuning.

• Solid Python or similar development skills (data processing, model building, evaluation pipelines).

• Experience working with JSON schema design and automated test frameworks.

• Familiarity with ML frameworks such as PyTorch, TensorFlow, HuggingFace or similar libraries.

• Experience with building or integrating ML pipelines into production-quality tools (API services, microservices, or batch systems).

• Strong understanding of software testing concepts: test cases, assertions, conditions, flows, automation logic.

• Ability to collaborate with cross-functional engineering teams and translate ambiguous test definitions into structured logic.

Educational Background:

• Bachelor's Degree (or higher) in Computer Science, Management Information Systems or related discipline, or equivalent professional work experience

Added Bonus:

• Experience with automated test frameworks used in embedded or multimedia systems.

• Experience with model fine-tuning using enterprise datasets.

• Background in building developer tooling, code generation, or compiler/AST-type transformations.

• Familiarity with LEAP/MM automation concepts or previous exposure to internal test automation pipelines.

• Experience implementing AI tools in enterprise environments requiring governance and model approval.