Responsibilities

• Build and improve AI-powered product features, including assistants, RAG capabilities, workflow automations, and fiscal insight-generation features.
• Develop AI application components such as data ingestion, retrieval, prompt orchestration, structured outputs, evaluation support, and monitoring hooks.
• Work with tax/domain experts to ensure AI outputs are accurate, explainable, grounded in fiscal data, and useful to users.
• Support evaluation and improvement of AI systems by reviewing model behavior, feedback, test cases, and production signals.
• Collaborate with product, frontend, and engineering colleagues to turn AI capabilities into usable product experiences.

Requirements

• Experience as a software engineer, AI engineer, data engineer, machine learning engineer, or similar role.
• Good Python skills and experience building backend, data-driven, automation, or AI/LLM-powered application components.
• Familiarity with LLM application patterns such as RAG, embeddings, vector search, prompt engineering, structured outputs, and context management.
• Experience or strong interest in AI orchestration frameworks such as Pydantic AI, LangChain, LangGraph, or similar tools.
• Ability to work with structured or semi-structured data to generate insights, summaries, recommendations, or decision-support features.
• Basic understanding of evaluation, monitoring, testing, secure development, data privacy, and responsible AI principles.
• Familiarity with C#, .NET, Angular, or TypeScript is a plus, but deep expertise is not expected.