CirrusLabs - Lead AI Administrator - Google Gemini

Role : AI Admin Lead Gemini

Experience : 7- 14 years

Location : Remote

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 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 : 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)