Staff AI Platform Engineer

Laurel

22h • Hybrid

About The Position

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.

Requirements

• 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 (REQUIRED)
• You’ve helped other engineers become more effective—through code reviews, system design, or introducing better tools and practices.
• Ownership mindset (REQUIRED)
• You don’t stop at “it works.” You care about adoption, performance, cost, and long-term maintainability.

Nice To Haves

• Experience building agentic systems or multi-step LLM workflows (tool use, planning, memory, etc.)
• Experience with RAG architectures at scale, including retrieval quality, indexing strategies, and evaluation
• Familiarity with model evaluation frameworks (offline + online), including human-in-the-loop or weak supervision approaches
• Experience optimizing LLM cost/latency tradeoffs (routing, batching, caching, model selection, etc.)
• Exposure to data infrastructure (e.g., pipelines, data lakes/warehouses, real-time processing)
• Experience with vector databases and search systems (e.g., Pinecone, Weaviate, Elasticsearch, etc.)
• Familiarity with AI safety, alignment, or compliance considerations in production systems
• Experience working in high-growth startup environments
• Background in legal tech, productivity tools, or enterprise SaaS

Responsibilities

• 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.

Benefits

• To date, we've secured significant funding from renowned venture capitalists (Google Ventures, IVP, Anthos, Upfront Ventures), as well as notable individuals like Marc Benioff, Gokul Rajaram, Kevin Weil, and Alexis Ohanian
• A smart, fun, collaborative, and inclusive team
• Great employee benefits, including equity and 401K
• Bi-annual, in-person company off-sites, in unique locations, to grow and share time with the team
• An opportunity to perform at your best while growing, making a meaningful impact on the company's trajectory, and embodying our core values: understanding your "why," dancing in the rain, being your whole self, and sanctifying time

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed