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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Platform Admin Lead - **Company:** ITSYNTAX INC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Frameworks, Audit Trail, User Authentication, Microsoft Azure, Cloud Computing, System Configuration, DevOps, Identity and Access Management, Google Cloud, System Availability, Large Language Models, Grafana, Software Troubleshooting, AI Platforms, Machine Learning Operations, Api Design, GPT, Api Management - **Published:** June 5, 2026 - **Apply:** https://www.dice.com/job-detail/c919ed88-d51e-463a-b52f-2432fd0c2d19 ## About the Role 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, Google Cloud Platform) 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 ## Description 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., 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 ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [#90DaysOfDevOps - The DevOps Learning Journey](https://www.wearedevelopers.com/videos/548-90daysofdevops-the-devops-learning-journey) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)