Staff AI Corporate Engineer

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.