• Develop and maintain Python components for text preprocessing, model invocation, prompt management, structured output validation, and coding workflows.
• Implement approved changes to prompts, model configuration, dictionaries, rules, and supporting code in small, version-controlled increments.
• Build pilots using LLMs, fuzzy matching, direct-match dictionaries, or hybrid approaches; adapt implementations to survey-specific taxonomies and requirements.
• Write unit, integration, regression, negative, and edge-case tests, and work with the evaluation team to compare candidate results with approved baselines.
• Reproduce production problems, isolate causes across code, data, prompts, and model behavior, and implement verified corrections.
• Partner with the MLOps Engineer on packaging, deployment, rollback, and post-release verification within Government-approved AWS environments.
• Participate in code reviews and SME working sessions; maintain technical documentation, user guidance, and reproducible examples for Government handoff.