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.

Position Overview

We are seeking a Corporate AI Engineer to join our Business Technology team with a specialized focus on enterprise AI enablement and infrastructure. In this role, you will design and operate the internal software factory that empowers employees to build, test, and publish AI agents; manage the hosting infrastructure for AI-generated web experiences; help define and enforce company-wide AI standards; and own the core AI infrastructure layer — covering usage analytics, spend governance, settings configuration, and model management. You will be the connective tissue between cutting-edge AI tooling and every internal team that depends on it.

Key Responsibilities

1. Corporate AI Software Factory

• Design, build, and maintain the internal developer platform that enables employees to create, test, and publish AI agents and automated workflows.

• Develop self-service tooling, templates, and scaffolding so non-engineering teams can safely deploy AI-powered applications.

• Own the CI/CD pipelines specific to AI agent delivery, ensuring repeatable, auditable, and secure release processes.

• Build and manage hosting infrastructure for AI-generated and AI-assisted web pages and internal portals.

2. AI Standards & Governance

• Establish guardrails for model access, data handling, prompt safety, and output validation across internal AI deployments.

• Act as an internal subject-matter expert and advisor, educating teams on best practices for responsible AI integration.

• Maintain a living AI standards playbook, updated as models, regulations, and organizational needs evolve.

3. AI Infrastructure & Platform Engineering

• Own and operate the company's central AI infrastructure layer, including usage dashboards, spend tracking, and budget alerting.

• Manage model configurations, API gateway settings, rate limits, and version-management across multiple AI providers.

• Implement observability tooling (logging, tracing, cost attribution) for all AI workloads to provide clear visibility to stakeholders.

• Evaluate and onboard new AI models, tools, and providers, managing the full lifecycle from pilot to production.

• Design and maintain the MCP (Model Context Protocol) server ecosystem, enabling structured tool-use and agent-to-service integrations.

4. Internal User Enablement

• Partner with business units to identify AI automation opportunities and translate them into production-ready tooling.

• Provide technical support, documentation, and training to internal builders using the AI platform.

• Maintain developer documentation, runbooks, and onboarding guides for the corporate AI ecosystem.

Required Qualifications

• 3–6 years of software engineering experience in a corporate or enterprise environment.

• Hands-on experience with AI ecosystem enablement, including one or more of: Claude (Anthropic), OpenAI Codex / GPT APIs, AI agent frameworks, and MCP (Model Context Protocol) integrations.

• Proficiency building and operating internal developer platforms, software factories, or CI/CD infrastructure.

• Experience with cloud infrastructure (AWS, Azure, or GCP), container orchestration (Kubernetes/Docker), and infrastructure-as-code (Terraform or similar).

• Solid understanding of API gateway patterns, rate limiting, authentication/authorization (OAuth2, API keys, RBAC).

• Demonstrated ability to translate governance requirements (security, compliance, policy) into technical controls.

• Strong communication skills — able to write clear documentation and present technical concepts to non-technical stakeholders.

Preferred Qualifications

• Direct experience with Anthropic Claude APIs, Claude.ai for Teams/Enterprise, or building Claude-powered agents.

• Familiarity with MCP server development and integration patterns for agentic tool-use.

• Exposure to AI model management lifecycle: fine-tuning, evaluation, versioning, and rollback strategies.

• Experience with observability stacks (Datadog, Grafana, OpenTelemetry) applied to LLM / AI services.

• Prior role as an internal platform or DevOps engineer supporting developer communities.

AI Ecosystem Familiarity (Desired)

Candidates should have working knowledge of — or be eager to rapidly develop expertise in — the following technologies:

• Claude (Anthropic) — API usage, prompt engineering, Claude.ai Enterprise administration

• MCP (Model Context Protocol) — server authoring, tool definitions, agent-to-service wiring

• OpenAI Codex / GPT APIs — integration patterns, function calling, fine-tuning pipelines

• AI Agents & Orchestration — multi-step reasoning agents, tool-use loops, agentic workflows

• OpenClaw — open-source AI tooling and interoperability frameworks

Why join Laurel:

• 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

We encourage diverse perspectives and rigorous thinkers who aren't afraid to challenge the status quo. Laurel is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We are not able to support visa sponsorship or relocation assistance. 

If you think you'd be a good fit for this role, we encourage you to apply, even if you don’t perfectly match all the bullet points in the job description. At Laurel, we strive to create an inclusive culture that encourages people from all walks of life to bring their unique, diverse perspectives to work. Every day, we aim to build an environment that empowers us all to do the best work of our careers, and we can't wait to show you what we have to offer!

Requires 3–6 years of software engineering experience, AI ecosystem enablement, internal platforms or CI/CD, cloud infrastructure, Kubernetes or Docker, infrastructure as code, API gateways, security controls, and strong communication.

Key Responsibilities

• building platforms
• enforcing standards
• managing infrastructure

Skills & Tools

Claude, Anthropic, OpenAI Codex, GPT APIs, Model Context Protocol (MCP), AWS, Azure, GCP, Kubernetes, Docker, Terraform, OAuth2, API keys, RBAC, Datadog, Grafana, OpenTelemetry, OpenClaw

Job Details

• Category: Engineering
• Seniority: Mid Level
• Commitment: Full Time
• Workplace: Remote — United States
• Salary: USD 191,000 – 285,000 / year
• Languages: English

Benefits

• 401k matching
• Retirement plan

About Laurel

An AI time platform that helps professional services firms capture, analyze, and optimize work time. — Industry: Information Technology