3 hours ago
Remote, United StatesStaff+
Base Salary
$191k - $285k/yr
Responsibilities
- Design, build, and maintain an internal developer platform for creating, testing, and publishing AI agents and automated workflows.
- Develop self-service tooling, templates, and scaffolding that enable non-engineering teams to deploy AI-powered applications safely.
- Own AI-agent delivery pipelines and ensure repeatable, auditable, and secure release processes.
- Build and manage hosting infrastructure for AI-generated and AI-assisted web pages and internal portals.
- Establish company-wide guardrails for model access, data handling, prompt safety, and output validation.
- Advise and educate internal teams on responsible AI integration and maintain the company AI standards playbook.
- Operate central AI infrastructure including usage dashboards, spend tracking, budget alerts, model configuration, API gateway settings, rate limits, and version management.
- Implement logging, tracing, and cost attribution for AI workloads.
- Evaluate and onboard AI models, tools, and providers from pilot through production.
- Design and maintain the MCP server ecosystem for structured tool use and agent-to-service integrations.
- Partner with business units to identify AI automation opportunities and deliver production-ready tooling.
- Provide technical support, documentation, training, runbooks, and onboarding guides for internal AI platform users.
Requirements
- 3–6 years of software engineering experience in a corporate or enterprise environment.
- Hands-on experience with AI ecosystem enablement, including Claude, OpenAI Codex or GPT APIs, AI agent frameworks, or MCP integrations.
- Experience building and operating internal developer platforms, software factories, or CI/CD infrastructure.
- Experience with AWS, Azure, or GCP; Kubernetes or Docker; and Terraform or similar infrastructure-as-code tools.
- Understanding of API gateway patterns, rate limiting, OAuth2, API keys, and RBAC.
- Ability to translate security, compliance, and policy requirements into technical controls.
- Strong communication skills for documentation and presenting technical concepts to non-technical stakeholders.
- Preferred experience with Anthropic Claude APIs, Claude.ai for Teams or Enterprise, or Claude-powered agents.
- Familiarity with MCP server development and agentic tool-use integration patterns.
- Exposure to AI model lifecycle management, including fine-tuning, evaluation, versioning, and rollback strategies.
- Experience with Datadog, Grafana, or OpenTelemetry for LLM and AI service observability.
- Prior experience as an internal platform or DevOps engineer supporting developer communities.
- Working knowledge of or willingness to develop expertise in OpenClaw and AI agent orchestration.
Benefits
- Equity and 401(k) benefits are provided.
- Bi-annual in-person company off-sites are held in unique locations.
- The company offers a collaborative and inclusive team environment.
- Visa sponsorship and relocation assistance are not available.
Tech Stack
Categories
About Laurel
Laurel is the world’s first AI Time platform for professional services firms. The company's AI transforms how organizations track, analyze, describe, and optimize their most valuable resource: time. By automating work time and connecting time data to business outcomes, Laurel enables firms to increase profitability, improve client delivery, and make data-driven strategic decisions. Founded in 2018, Laurel serves many of the world's largest accounting, consulting and law firms.