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Laurel is an AI-driven time intelligence platform serving major professional services firms (EY, Aprio, Crowell & Moring, Frost Brown Todd) that processes over 1 billion work activities annually. The company uses proprietary machine learning to help accounting and law firms capture, analyze, and optimize time data to increase profitability and improve client delivery.
As a Senior Platform Engineer on the Foundational Engineering team, you will design and build the core infrastructure and systems powering Laurel's internal developer platform and production environments. You'll ensure high availability, scalability, and security of core services, enabling rapid and reliable product shipping across the organization.
Key responsibilities include:
- Design, build, and maintain robust, scalable, secure infrastructure systems supporting the AI-driven platform
- Manage and optimize cloud infrastructure (AWS and Azure) and Kubernetes container orchestration
- Build and maintain high-performance CI/CD pipelines to increase deployment frequency, security, and reliability
- Implement comprehensive observability, monitoring, and alerting; establish on-call and incident response patterns
- Partner with engineering teams to diagnose performance bottlenecks and optimize cost-efficiency
- Develop internal tooling to automate infrastructure provisioning and streamline development
- Stay current with industry trends and emerging technologies
You'll work closely with Security, Developer Productivity, Data Infrastructure, and product-focused engineering teams. The role tackles complex distributed systems problems—measuring performance of non-deterministic AI systems, balancing cost/speed/quality tradeoffs, ensuring global reliability, and enabling safe experimentation.
Required qualifications: 4+ years in Platform, Infrastructure, SRE, or DevOps roles; independent architecture and shipping of complex systems; deep experience with APIs, distributed systems, cloud infrastructure, and data-intensive applications; Kubernetes and AWS expertise; development experience with Terraform, Go, and TypeScript; startup environment experience; significant Linux administration; Git familiarity; regular on-call rotation participation; CI tooling and build systems experience; production debugging with logs, metrics, and tracing.
Nice-to-haves include AI systems deployment in enterprise environments, Azure experience, software engineer background with systems engineering, familiarity with Argo, cdk8s, OpenTelemetry, MongoDB, PostgreSQL, Spacelift, CircleCI, GitHub Actions, and enterprise authentication/security systems.
