Lead GenAI SaaS / Platform Engineer

Accountabilities: GenAI Platform Administration: Own the end-to-end administration, configuration, governance, and lifecycle management of enterprise generative AI platforms, including ChatGPT Enterprise, Claude, and other internal AI solutions. Platform Architecture & Scalability: Design and maintain scalable SaaS architectures that support enterprise-wide AI adoption, ensuring platform reliability, performance, and operational efficiency. Integrations & Extensibility: Develop and implement Model Context Protocol (MCP) connectors, REST API integrations, and secure data pipelines to connect LLM platforms with enterprise applications, systems, and business tools. Identity & Access Management: Establish and maintain enterprise-grade authentication and authorization frameworks using SAML 2.0, SCIM provisioning, OAuth, and role-based access control (RBAC), leveraging Okta and Microsoft Entra ID. Security & AI Governance: Define and enforce security policies, data privacy controls, compliance requirements, and responsible AI usage guidelines to ensure secure and controlled adoption of generative AI technologies. Automation & Scripting: Develop automation scripts and operational workflows using Python or PowerShell to streamline user provisioning, platform configuration, usage monitoring, and policy enforcement. Platform Monitoring & Reliability: Monitor platform health, availability, performance, and usage across enterprise environments, identifying operational risks and implementing preventive improvements. Incident & Escalation Management: Lead complex technical troubleshooting and Tier 3 incident escalations, ensuring timely resolution and minimizing service disruptions. Consumption & License Management: Monitor AI platform consumption, licensing metrics, user activity, and operational costs to optimize resource utilization and platform efficiency. Cloud Infrastructure Operations: Support reliable platform operations across AWS and Azure environments, ensuring appropriate logging, monitoring, security, and infrastructure integration. Cross-Functional Collaboration: Partner with Security, Workplace IT, endpoint engineering, and MDM teams to coordinate platform requirements and align SaaS architecture with enterprise technology standards. Continuous Improvement: Stay informed about emerging LLM technologies, AI integration standards, and SaaS engineering practices to continuously improve enterprise AI capabilities. Requirements 8–12 years of professional experience in Enterprise SaaS Engineering, Cloud Infrastructure, Platform Engineering, or Enterprise Platform Administration. Strong hands-on experience designing, implementing, and managing enterprise SaaS platforms and complex technical environments. Identity & Access Management: Deep understanding of modern IAM architectures, including Okta, Microsoft Entra ID, Single Sign-On (SSO), SAML 2.0, SCIM provisioning, OAuth flows, and role-based access control (RBAC). Generative AI & LLM Platforms: Practical familiarity with enterprise generative AI platforms, LLM toolchains, AI integrations, and enterprise AI governance frameworks. Experience administering ChatGPT Enterprise, Claude Enterprise, or comparable enterprise AI platforms is a significant advantage. Knowledge of emerging AI integration standards, particularly Model Context Protocol (MCP), and their application in enterprise environments. Programming & Automation: Strong proficiency in Python or PowerShell, with demonstrated experience building automation scripts and managing operational workflows. API Integration: Hands-on experience with REST APIs, API authentication, system integrations, and secure data exchange between enterprise applications. Cloud Technologies: Solid understanding of AWS or Microsoft Azure, including cloud infrastructure, enterprise services, and platform operations. Monitoring & Incident Management: Experience with enterprise logging, monitoring, platform health management, troubleshooting, and complex incident resolution. Security & Compliance: Strong understanding of enterprise security principles, data privacy, access governance, and least-privilege security models. SaaS Operations: Experience managing platform configurations, user provisioning, licensing, consumption metrics, and enterprise software lifecycle activities. Collaboration: Ability to work effectively with cross-functional teams, particularly Security, Workplace IT, infrastructure, and endpoint engineering. Leadership & Communication: Strong problem-solving, organizational, and communication skills, with the ability to take technical ownership and guide enterprise platform initiatives. A proactive mindset, adaptability, and enthusiasm for learning emerging generative AI technologies are essential. Benefits Fully remote working arrangement within India. Full-time employment opportunity. Opportunity to work on enterprise-scale generative AI platforms and emerging LLM technologies. Exposure to advanced AI solutions, including ChatGPT Enterprise, Claude, and MCP integrations. Opportunity to lead strategic initiatives in enterprise AI architecture, platform engineering, and governance. Professional growth through hands-on experience with modern SaaS platforms, cloud infrastructure, and enterprise security technologies. Collaborative environment involving cross-functional teams and global enterprise operations. Opportunity to influence AI adoption strategies and build scalable, secure, and innovative technology solutions.