Staff AI Platform Engineer

Staff AI Platform Engineer Laurel is on a mission to return time. As the leading AI Time platform for professional services firms, we’re transforming how organizations capture, analyze, and optimize their most valuable resource: time. Our proprietary machine learning technology automates work time capture and connects time data to business outcomes, enabling firms to increase profitability, improve client delivery, and make data-driven strategic decisions. We serve many of the world's largest accounting and law firms, including EY, Aprio, Crowell & Moring, and Frost Brown Todd, and process over 1 billion work activities annually that have never been collected and aggregated before Laurel’s AI Time platform. Our team comprises top talent in AI, product development, and engineering—innovative, humble, and forward-thinking professionals committed to redefining productivity in the knowledge economy. We're building solutions that empower workers to deliver twice the value in half the time, giving people more time to be creative and impactful. If you're passionate about transforming how people work and building a lasting company that explores the essence of time itself, we'd love to meet you. ABOUT THE ROLE: As a Staff AI Platform Engineer, you will lead efforts to build out Laurel’s AI platform to be worldclass. We already process millions of inferences per day, but to keep up with our growth, we need a platform to power not only hundreds of millions, but agentic workflows, LLM heavy features, RAG designs, etc.. You’ll collaborate closely with cross-functional teams to design and deploy a cutting-edge AI platform. WHAT YOU WILL DO: - Own business‑critical AI challenges. Partner with product, design, and engineers to uncover the real customer problems, then frame them as tractable projects supported by a AI platform. - Build end‑to‑end solutions. Harden and build out our AI platform to be world class. This includes a platform that supports full agentic capabilities and is heavily LLM reliant. - Ship incrementally, learn rapidly. Break ambitious ideas into testable slices, measure impact, and iterate. Curiosity drives you to ask the right questions; pragmatism drives you to deliver value week over week. - Elevate the team. Mentor engineers on best practices in AI engineering, model evaluation, prompt design, and responsible AI. Introduce tools and techniques that improve reliability, speed of deployment, fairness, and performance. - Take true ownership. We empower every team member to understand the business levers behind their work and to push for outcomes—not just tickets. You’ll have the autonomy to choose the right approach and the accountability for results. YOU WILL BE A GREAT FIT IF YOU HAVE: - Deep experience building AI/ML platforms at scale (REQUIRED) You’ve built or significantly contributed to platforms that serve high-volume inference (millions+ per day), with strong opinions on reliability, latency, cost, and observability. - Strong backend / distributed systems fundamentals (REQUIRED) You are fluent in designing and operating distributed systems (e.g., microservices, async pipelines, streaming, queueing systems) and can reason about tradeoffs under real production constraints. - Hands-on experience with LLMs in production (REQUIRED) You’ve built and shipped LLM-powered systems beyond prototypes—prompting, evaluation, latency optimization, caching, fallbacks, and cost control are all familiar problems. - Experience designing AI infrastructure, not just models (REQUIRED) You think in terms of platforms: orchestration layers, evaluation frameworks, feature stores, model/version management, and developer tooling—not just individual models or experiments. - Proven ability to operate in fast-moving, ambiguous environments (REQUIRED) You’ve worked in environments where the roadmap is evolving, and you’re comfortable making decisions with incomplete information. - Experience mentoring and raising the bar (REQU ... (truncated, view full listing at source)