Principal AI Engineer

Role overview Set the technical direction for AI features in an enterprise document automation product, while remaining hands-on in design and software delivery. The role spans AI architecture, production engineering, safe adoption of AI across development, and technical leadership in a regulated customer environment.

Responsibilities - Define an AI architecture and delivery roadmap covering model use, orchestration, retrieval, evaluation, cost, and response time. - Build AI capabilities from prototype through production using .NET and React, with attention to security, performance, and maintainability. - Establish evaluation methods, guardrails, monitoring, and governance to support reliable and explainable AI behavior. - Guide the use of AI tools across software development, including coding, testing, review, and documentation workflows. - Improve delivery pipelines to track model and prompt versions, run evaluations, monitor systems, and manage costs. - Mentor engineers and work with product, security, architecture, and customer teams to shape priorities and technical decisions.

Requirements - 12+ years of software development experience, including principal, staff, or lead-level technical leadership. - Strong hands-on experience with C#/.NET Core and React/TypeScript or a comparable single-page application framework. - A track record of delivering production AI systems, including LLM integration, retrieval-augmented generation, prompt design, and agents or tool-calling. - Experience with cloud AI services, REST APIs, Entity Framework, and Azure SQL or SQL Server. - Ability to evaluate AI quality with test sets, benchmarks, human review, and methods suited to non-deterministic systems. - Knowledge of web and AI security, including prompt injection and protection of sensitive data; experience with Git and CI/CD. - Strong communication and mentoring skills, with experience influencing architecture and roadmap decisions.

Nice to have Experience with model fine-tuning, vector databases, AI observability, multi-agent systems, or AI/ML pipelines; Office add-ins; legacy .NET or WPF; OAuth or SSO; Redis; Linux and Docker; PowerShell; performance diagnostics; infrastructure automation; or enterprise software in legal, financial, or compliance-focused settings.

Benefits and work setup Remote-first work with optional in-person sessions, a learning-focused culture, and opportunities to shape enterprise AI strategy and grow technically. The work supports automation of important document and compliance processes.