What are the responsibilities and job description for the ChatGPT Enterprise / GenAI Platform Operations Lead (W2 Candidate Only) position at Metalight Solutions Inc?
Job Title: ChatGPT Enterprise / GenAI Platform Operations Lead
Location: Chicago, IL (3days On-Site, 2days Remote)
Employment Type: Contract (W2 Candidate only)
Position Overview
We are looking for an experienced GenAI Platform Operations / SRE Lead to manage and operate enterprise-scale AI platforms, with a strong focus on ChatGPT Enterprise, OpenAI APIs, Codex, AI governance, security, monitoring, and platform reliability.
The ideal candidate will combine a strong background in SRE, CloudOps, IT Operations, or Platform Engineering with hands-on experience supporting Generative AI / LLM platforms. This role will be responsible for enterprise ChatGPT administration, AI platform security, Codex workspace operations, usage and credit optimization, monitoring, governance, and leading distributed/offshore teams.
Key Responsibilities
ChatGPT Enterprise Platform Administration & Security
- Manage the enterprise ChatGPT administration environment, including domain verification, SSO/SAML, user provisioning, onboarding, and access management.
- Implement and maintain security, privacy, compliance, and data protection controls to minimize enterprise data leakage risks.
- Manage RBAC and permissions for custom GPTs, APIs, Codex/developer workspaces, and other AI platform capabilities.
- Establish and maintain governance standards for enterprise AI usage.
- Partner with security and compliance teams to implement responsible AI and risk mitigation practices.
Codex Agent & Workspace Operations
- Provision, monitor, and manage local and cloud-based development environments used by autonomous Codex agents.
- Support AI agents performing code migration, refactoring, testing, and multi-file development workflows.
- Establish governance around agent workflows, hooks, discovery surfaces, and third-party integrations.
- Monitor agent execution, token consumption, resource utilization, execution timelines, and failure patterns.
- Establish controls to prevent infinite loops, excessive resource consumption, or uncontrolled AI execution.
AI Usage, Financial & Credit Management
- Track AI platform usage, adoption, seat utilization, and consumption metrics.
- Analyze standard versus usage-based seats and optimize workspace allocation.
- Monitor and optimize AI platform credits and organizational consumption.
- Develop dashboards and reports measuring AI adoption, usage patterns, productivity, and platform health.
- Identify opportunities to reduce unnecessary consumption and improve platform ROI.
AI Operations / SRE
- Lead day-to-day AI platform monitoring, incident triage, troubleshooting, root-cause analysis, and operational support.
- Define operational thresholds, usage limits, policies, alerts, and escalation procedures.
- Apply ITSM, ITIL, and SRE principles to enterprise AI operations.
- Develop operational runbooks, incident management processes, service-level objectives, and continuous improvement frameworks.
- Monitor AI platform health and performance using tools such as Dynatrace, Datadog, or similar platforms.
AI Process & Prompt Optimization
- Design reusable frameworks for AI operational processes and platform optimization.
- Guide engineering and business teams on prompt engineering and effective GenAI usage.
- Analyze AI usage patterns and recommend improvements to workflows, policies, and platform configuration.
- Support AI evaluation, responsible AI, risk mitigation, and quality improvement initiatives.
Team & Stakeholder Leadership
- Lead and mentor distributed/offshore AI Operations, SRE, CloudOps, or Platform Engineering teams.
- Establish engineering standards, operational procedures, and code/workflow quality practices.
- Act as a liaison between business stakeholders, engineering teams, security/compliance teams, and OpenAI/vendor teams.
- Communicate platform health, incidents, adoption, risks, and operational metrics to technical and business leadership.
Required Qualifications
- 7 10 years of experience in SRE, IT Operations, CloudOps, DevOps, Platform Engineering, or related disciplines.
- 1 2 years of hands-on experience with Generative AI / LLM platforms.
- Experience with OpenAI, ChatGPT Enterprise, OpenAI APIs, or Codex.
- Experience administering or operating enterprise cloud/platform environments.
- Experience with SSO/SAML, RBAC, identity/access management, and enterprise security controls.
- Strong understanding of ITSM, ITIL, SRE, incident management, monitoring, and operational processes.
- Experience leading offshore/distributed teams.
- Strong stakeholder management and communication skills.
Technical Skills
Required / Strongly Preferred
- ChatGPT Enterprise
- OpenAI APIs
- Custom GPTs
- OpenAI Assistants / agent-based APIs
- Codex
- GenAI / LLM platforms
- AI Operations / LLMOps
- SRE / Platform Engineering
- ITSM / ITIL
- RBAC / SSO / SAML
- Cloud platforms Azure preferred, AWS or Google Cloud Platform
- Monitoring / Observability Dynatrace, Datadog, or similar
AI Frameworks
Experience with one or more:
- LangChain
- LangGraph
- CrewAI
- Other agentic AI / LLM orchestration frameworks
Nice to Have
- Azure OpenAI
- LLMOps frameworks
- AI evaluation frameworks/tools
- Responsible AI / AI governance
- AI security and risk management
- OpenAI / Azure certifications
- Experience managing enterprise AI adoption and FinOps/AI consumption