About the job:
As part of our Enterprise AI Engineering Team within the Enterprise Delivery Enablement Organization, we are delivering cutting-edge solutions to empower our developer community. Our client has recently signed major enterprise contracts to integrate premier AI models into their ecosystem.
We are seeking a highly motivated and technically skilled Senior AI Platform Engineer to lead the initial setup, long-term maintenance, and performance optimization of these AI platforms. In this role, you will stand up and manage emerging AI capabilities (including generative AI and GitHub Copilot) across the enterprise environment. The ideal candidate will have deep senior-level experience deploying enterprise SaaS platforms at scale and the development skills necessary to build comprehensive telemetry, reporting, and cost-usage dashboards.
Minimum qualifications:
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- 8+ years of experience supporting enterprise technology platforms or SaaS products.
- 3+ years of experience implementing, administering, or monitoring AI, cloud, or collaboration platforms (health, availability, performance).
- Experience deploying enterprise SaaS solutions at scale.
- Strong scripting, development, and automation experience using languages such as Python, PowerShell, or similar for infrastructure management, system integration, and process automation.
- Experience extracting, transforming, and analyzing data from APIs, databases, cloud services, and enterprise systems to build reporting and dashboards (specifically to show usage and spend).
- Strong knowledge of enterprise components and security, including Identity and Access Management (IAM), Single Sign-On (SSO), Entra ID / Azure AD, SAML, OAuth, OpenID Connect, and Role-Based Access Control (RBAC).
- Experience with monitoring, alerting, and analysis tools such as Splunk and Grafana.
- Experience managing production support, incident management, and operational processes.
Preferred qualifications:
- Experience implementing or administering specific enterprise AI platforms, such as Anthropic Enterprise, OpenAI Enterprise, GitHub Copilot Enterprise, Microsoft Copilot, or Azure AI Foundry.
- Experience with AI governance, compliance, and model management.
- Familiarity with FinOps, cost management, budgeting, and usage analytics.
- Knowledge of software deployment and enterprise application management practices.
- Excellent communication and stakeholder management skills.
Responsibilities:
- Lead the end-to-end deployment, initial setup, and integration of enterprise AI platforms and services.
- Own the day-to-day administration and operational support of AI platforms, ensuring long-term maintenance and peak performance.
- Monitor platform health, availability, performance, and usage trends.
- Manage vendor escalations and coordinate the resolution of platform issues.
- Develop runbooks, operational procedures, support documentation, and knowledge articles.
- Drive platform lifecycle management, upgrades, feature enablement, and decommissioning activities.
- Define support models, service level objectives, and operational metrics.
- Develop user onboarding, training, and enablement programs.
- Develop and maintain automation scripts (Python, PowerShell, etc.) to streamline AI platform operations, infrastructure provisioning, system integrations, and workflows.
Design and execute data extraction and transformation processes from enterprise systems, APIs, databases, and cloud platforms to support operational reporting, usage analytics, and spend dashboards.
