Principal AI Engineer

Drake Software is a leading digital tax filing platform seeking a Principal AI Engineer to architect, build, and scale production-grade AI systems across Taxwell. This role involves translating emerging AI capabilities into secure, reliable, and scalable systems that have measurable business impact.

Responsibilities:

• Architect and deploy production LLM-powered systems across engineering, operations, tax, compliance, analytics, and customer workflows
• Design and operate retrieval-augmented generation (RAG) systems grounded in proprietary documentation, structured data, and internal knowledge
• Build shared AI infrastructure (model routing, evaluation pipelines, guardrails, observability, caching, cost controls) to enable safe and scalable AI adoption across teams
• Implement agentic and workflow-driven systems using frameworks such as LangChain, LangGraph, ADK, or similar, with clear state management and error handling
• Evaluate and integrate commercial and open-weight models based on performance, latency, cost, and compliance constraints
• Establish rigorous evaluation frameworks (retrieval metrics, groundedness, latency, hallucination mitigation) and production monitoring standards
• Embed AI into customer-facing products to improve personalization, accuracy, and user outcomes
• Partner with platform, DevOps, and security teams to ensure reliability, scalability, governance, and regulatory compliance
• Drive experimentation and telemetry to measure system impact and continuously improve performance

Requirements:

• 10+ years of software engineering experience, including 3+ years at Staff or Principal level with architectural ownership
• Proven track record building and operating production AI systems serving real users at scale
• Deep hands-on experience with LLM systems, including RAG architecture, agent orchestration, embeddings, and evaluation methodologies
• Familiarity with vector databases and embeddings (e.g., Pinecone, FAISS, Chroma)
• Proficiency in Python and/or TypeScript
• Experience integrating AI with enterprise APIs, structured data sources, and knowledge systems
• Strong architectural judgment balancing rapid iteration with production reliability and cost discipline
• Experience building internal AI platforms or enterprise copilots
• Experience delivering customer-facing AI features at scale
• Experience in regulated industries (fintech, tax, healthcare)
• Experience fine-tuning or adapting open-weight LLMs and optimizing inference performance