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, Tensor Flow, Hugging Face 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.