Senior/Staff Forward Deployed Engineer

About the role

At Laurel, we are on a mission to return time to professional services firms by transforming how organizations capture, analyze, and optimize their most valuable resource: time. As the leading AI Time platform, we use proprietary machine learning technology to automate work time capture and connect time data to business outcomes. This enables 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 are 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 are passionate about transforming how people work and building a lasting company that explores the essence of time itself, we would love to meet you.

This role is for a You will work directly with customers and Laureates to design, build, and deploy AI-powered systems that solve real operational problems in professional services environments. You will operate at the intersection of engineering, product, and customer delivery, embedding deeply with customer teams to understand their workflows firsthand. This is not a solutions architect role, not post-sales support, and not lightweight integration work; you will write production code and own technical outcomes end-to-end. The best FDEs are highly technical product engineers who also happen to be exceptional at navigating ambiguity and communicating with stakeholders. You should be excited by questions about turning messy operational workflows into reliable AI systems and about what breaks when LLMs meet real enterprise data. You will help shape the core Laurel platform through what you learn in the field and accelerate how quickly teams deliver trusted production workflows.

What you'll do

Work directly with customers and Laureates to understand operational workflows, constraints, and technical environments. Design and implement production-grade solutions across backend services, orchestration layers, integrations, and internal tooling. Write high-quality code across the stack - typically TypeScript, APIs, data pipelines, and cloud infrastructure. Own deployments end-to-end: discovery, architecture, implementation, testing, rollout, monitoring, and iteration. Debug complex issues across customer systems, infrastructure, authentication, APIs, and data pipelines. Collaborate closely with Product and Core Engineering to turn field learnings into reusable platform capabilities. Rapidly prototype new functionality while maintaining strong engineering judgment around scalability and maintainability. Translate ambiguous customer needs into clear technical plans and execution paths. Help customers operationalize AI safely and effectively in real production environments. Help accelerate the implementation team's efforts to reduce time to impact for customers.

Requirements

We are looking for engineers who combine strong technical fundamentals with exceptional ownership and execution. You may be a fit if you have a minimum of 4+ years of experience building production software systems and are comfortable moving across backend, infrastructure, integrations, and customer environments. You must be able to independently architect and ship complex systems with minimal oversight and have experience with APIs, distributed systems, cloud infrastructure, and data-intensive applications. You should have worked with LLMs, AI agents, retrieval systems, orchestration frameworks, or applied AI systems in production, and you must thrive in ambiguous environments where requirements evolve quickly. You must be able to communicate clearly with both engineers and non-technical stakeholders and care deeply about speed, iteration, and customer impact. You must be excited to work directly with customers and own outcomes, not just tickets.

Strong signals that correlate with success in this role include startup experience or early-stage product building, experience deploying AI systems into enterprise environments, a strong systems engineering or infrastructure background, experience integrating with third-party enterprise systems and APIs, and familiarity with authentication systems and security constraints.

Practical notes: This role may require travel, and specific hours or deadlines will be defined in offer discussions and team agreements.

Location: Hybrid

Engagement: Full-time