Description
We are looking for an AI Software Engineer to help expand AI capabilities across our tax-focused product ecosystem. The role supports our AI-powered tax assistant but is broader than RAG alone: it also includes generative AI features, workflow automation, and AI-powered insights from fiscal data.
Key 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.
- Work effectively in AWS AI-DLC workflows, using AI as an engineering collaborator while applying sound judgment, structured review, traceable decision-making, and human approval at critical points.
Experience and Skills
- 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.