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Laurel is an AI Time platform for professional services firms that automates work time capture and connects time data to business outcomes. The company serves major accounting and law firms (EY, Aprio, Crowell & Moring, Frost Brown Todd) and processes over 1 billion work activities annually.
As a Forward Deployed Engineer, you will work directly with customers to design, build, and deploy AI-powered systems that solve real operational problems. This role operates at the intersection of engineering, product, and customer delivery—you'll embed deeply with customer teams, understand their workflows firsthand, and ship production-grade systems that create measurable impact.
This is a hands-on engineering role, not a solutions architect or post-sales support position. You will write production code, own technical outcomes end-to-end, and help shape the core Laurel platform through field learnings.
Key responsibilities include:
- Work directly with customers 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, 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 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 production environments
- Accelerate implementation team efforts to reduce time to impact for customers
Success in this role means earning deep trust with customer teams through technical credibility, moving customers from pilot to production quickly, creating reusable technical patterns that improve the core platform, identifying the difference between one-off customization and durable product opportunity, bringing clarity to ambiguous problems, operating with urgency while maintaining strong engineering judgment, and leaving systems in a maintainable, scalable state.
REQUIREMENTS:
- Minimum 4+ years of experience building production software systems
- Comfortable moving across backend, infrastructure, integrations, and customer environments
- Can independently architect and ship complex systems with minimal oversight
- Experience with APIs, distributed systems, cloud infrastructure, and data-intensive applications
- Experience with LLMs, AI agents, retrieval systems, orchestration frameworks, or applied AI systems in production
- Thrive in ambiguous environments where requirements evolve quickly
- Can communicate clearly with both engineers and non-technical stakeholders
- Care deeply about speed, iteration, and customer impact
- Excited to work directly with customers and own outcomes
STRONG SIGNALS (not requirements but correlate with success):
- Startup experience or early-stage product building
- Experience deploying AI systems into enterprise environments
- Strong systems engineering or infrastructure background
- Experience integrating with third-party enterprise systems and APIs
- Familiarity with authentication systems, security constraints, and enterprise IT environments
- Experience debugging production issues in unfamiliar codebases
- History of shipping quickly under real-world constraints
- Comfort balancing rapid iteration with long-term engineering quality
