Note: The job is a remote job and is open to candidates in USA. Laurel is an AI Time platform company using machine learning to help professional services firms capture, analyze, and optimize work time. Laurel is seeking a Staff AI Corporate Engineer to build and operate its internal AI software factory, infrastructure, and governance systems. The role will enable employees to create and deploy AI agents, manage models and hosting infrastructure, establish responsible AI standards, and support internal teams.
Responsibilities
- 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
- 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
- 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
- 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
Skills
- • 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
- We are not able to support visa sponsorship or relocation assistance
- • Direct experience with Anthropic Claude APIs, [Claude.ai](http://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
- 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](http://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
Benefits
- Equity
- 401K
- Bi-annual, in-person company off-sites, in unique locations, to grow and share time with the team
Company Overview