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