AI Platform Admin Lead

Role overview :

Own the administration and operations of enterprise AI platforms, ensuring secure, scalable, and cost-efficient usage of LLM services. Act as the central point for platform governance, usage monitoring, and enablement of AI teams.

Key responsibilities :

- Administer and manage enterprise AI platforms including OpenAI, Anthropic Claude, or Google Gemini.

- Manage API access, keys, usage policies, and rate limits across teams and applications.

- Establish centralized governance for AI usage including audit trails, compliance controls, and policy enforcement.

- Monitor platform usage, performance, and costs; implement cost controls, budget tracking, and optimization strategies.

- Build and maintain dashboards for AI consumption, latency, and model performance analytics.

- Enable multi-model orchestration and routing across different LLM providers for resiliency and optimization.

- Define and enforce security controls including data privacy, prompt controls, and access management.

- Support platform onboarding for engineering and business teams, including SDK/API integrations and environment setup.

- Collaborate with AI/ML, DevOps, and security teams to operationalize AI workloads.

- Troubleshoot platform, API, and model-related issues; ensure high availability and reliability.

- Enable governance for agentic AI workflows, including identity, permissions, and operational guardrails.

- Drive platform standardization, best practices, and reusable frameworks across teams.

Required experience :

- 7+ years in platform engineering, cloud operations, or AI platform management.

- Hands-on experience with at least one : OpenAI (ChatGPT, Azure OpenAI), Anthropic Claude, or Google Gemini.

- Experience managing API-based platforms, including authentication, quotas, and usage monitoring.

- Strong understanding of LLM/GenAI architectures, token-based usage models, and AI application patterns.

- Experience in platform governance, cost optimization, and operational monitoring.

- Familiarity with cloud platforms (AWS, Azure, GCP) and AI services.

- Experience working with monitoring/observability tools and dashboards.

- Strong troubleshooting and operational support mindset.

Good to have :

- Experience with AI gateway/platforms or multi-provider orchestration (LLM routing, failover).

- Exposure to MLOps, CI/CD pipelines, and model lifecycle management.

- Knowledge of agentic AI systems, RAG architectures, and vector databases.

- Familiarity with security, compliance, and responsible AI frameworks.

- Scripting or automation experience (Python, APIs, Terraform).